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McCabe, Gregory J., and David M. Wolock. "Joint Variability of Global Runoff and Global Sea Surface Temperatures." Journal of Hydrometeorology 9, no. 4 (August 1, 2008): 816–24. http://dx.doi.org/10.1175/2008jhm943.1.
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Abstract Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905–2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Niño–Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Atlantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.
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Lv, Meizhao, Hui Lu, Kun Yang, Zhongfeng Xu, Meixia Lv, and Xiaomeng Huang. "Assessment of Runoff Components Simulated by GLDAS against UNH–GRDC Dataset at Global and Hemispheric Scales." Water 10, no. 8 (July 24, 2018): 969. http://dx.doi.org/10.3390/w10080969.
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The current evaluations of global land data assimilation system (GLDAS) runoff were generally limited to the observation-rich areas. At the global and hemispheric scales, we assessed different runoff components performance of GLDAS (1.0 and 2.1) using the University of New Hampshire and Global Runoff Data Centre (UNH-GRDC) dataset. The results suggest that GLDAS simulations show considerable uncertainties, particularly in partition of surface and subsurface runoffs, in snowmelt runoff modeling, and in capturing the northern peak time. GLDAS1.0-CLM (common land model) produced more surface runoff almost globally; GLDAS-Noah generated more surface runoff over the northern middle-high latitudes and more subsurface runoff in the remaining areas; while the partition in GLDAS1.0-VIC (variable infiltration capacity) is almost opposite to that in Noah. Comparing to GLDAS1.0-Noah, GLDAS2.1-Noah improved the premature snow-melting tendency, but its snowmelt-runoff peak magnitude was excessively high in June and July. The discrepancies in northern primary peak times among precipitation and runoff is partly caused by the combination of rainfall and melting-snow over high-latitude, as well as the very different temporal–spatial distributions for snowmelt runoff simulated by GLDAS models. This paper can provide valuable guidance for GLDAS users, and contribute to the further improvement of hydrological parameterized schemes.
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Smith, H. J. "CLIMATE SCIENCE: Charting Global Runoff." Science 320, no. 5884 (June 27, 2008): 1696d. http://dx.doi.org/10.1126/science.320.5884.1696d.
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Munier, S., H. Palanisamy, P. Maisongrande, A. Cazenave, and E. F. Wood. "Global runoff anomalies over 1993–2009 estimated from coupled Land–Ocean–Atmosphere water budgets and its relation with climate variability." Hydrology and Earth System Sciences 16, no. 10 (October 16, 2012): 3647–58. http://dx.doi.org/10.5194/hess-16-3647-2012.
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Abstract. Whether the global runoff (or freshwater discharge from land to the ocean) is currently increasing and the global water cycle is intensifying is still a controversial issue. Here we compute land–atmosphere and ocean–atmosphere water budgets and derive two independent estimates of the global runoff over the period 1993–2009. Water storage variations in the land, ocean and atmosphere reservoirs are estimated from different types of data sets: atmospheric reanalyses, land surface models, satellite altimetry and in situ ocean temperature data (the difference between altimetry based global mean sea level and ocean thermal expansion providing an estimate of the ocean mass component). These data sets are first validated using independent data, and then the global runoff is computed from the two methods. Results for the global runoff show a very good correlation between both estimates. More importantly, no significant trend is observed over the whole period. Besides, the global runoff appears to be clearly impacted by large-scale climate phenomena such as major ENSO events. To infer this, we compute the zonal runoff over four latitudinal bands and set up for each band a new index (combined runoff index) obtained by optimization of linear combinations of various climate indices. Results show that, in particular, the intertropical and northern mid-latitude runoffs are mainly driven by ENSO and the Atlantic multidecadal oscillation (AMO) with opposite behavior. Indeed, the zonal runoff in the intertropical zone decreases during major El Niño events, whereas it increases in the northern mid-latitudes, suggesting that water masses over land are shifted northward/southward during El Niño/La Niña. In addition to this study, we propose an innovative method to estimate the global ocean thermal expansion. The method is based on the assumption that the difference between both runoff estimates is mainly due to the thermal expansion term not accounted for in the estimation of the ocean mass. We find that our reconstructed thermal expansion time series compares well with two existing data sets in terms of year-to-year fluctuations but somewhat differs on longer (multi-year) time scales. Possible explanations include non negligible steric variations from the deep ocean.
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Munier, S., H. Palanisamy, P. Maisongrande, A. Cazenave, and E. F. Wood. "Global runoff over 1993–2009 estimated from coupled land-ocean-atmosphere water budgets and its relation with climate variability." Hydrology and Earth System Sciences Discussions 9, no. 4 (April 11, 2012): 4633–65. http://dx.doi.org/10.5194/hessd-9-4633-2012.
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Abstract. Whether the global runoff (or freshwater discharge from land to the ocean) is currently increasing and the global water cycle is intensifying is still a controversial issue. Here we compute land-atmosphere and ocean-atmosphere water budgets and derive two independent estimates of the global runoff over the period 1993–2009. Water storage variations in the land, ocean and atmosphere reservoirs are estimated from different types of datasets: atmospheric reanalyses, land surface models, satellite altimetry and in situ ocean temperature data (the difference between altimetry based global mean sea level and ocean thermal expansion providing an estimate of the ocean mass component). Results for the global runoff from the two methods show a very good correlation between both estimates. More importantly, no significant trend is observed over the whole period. Besides, the global runoff appears to be clearly impacted by large-scale climate phenomena such as major ENSO events. To infer this, we compute the zonal runoff over four latitudinal bands and set up for each band a new index (Combined Runoff Index) obtained by optimization of linear combinations of various climate indices. Results show that, in particular, the intertropical and northern mid-latitude runoffs are mainly driven by ENSO and the Atlantic Multidecadal Oscillation (AMO) with opposite behavior. Indeed, the zonal runoff in the intertropical zone decreases during major El Niño events whereas it increases in the northern mid-latitudes, suggesting that water masses over land are shifted northward/southward during El Niño/La Niña. In addition to this study, we propose an innovative method to estimate the global ocean thermal expansion. The method is based on the assumption that the difference between both runoff estimates is mainly due the thermal expansion term not accounted for in the estimation of the ocean mass. Comparison of our reconstructed thermal expansion with two existing datasets shows the relevance of this new method.
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Wiersma, Pau, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut. "Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff." Hydrology and Earth System Sciences 26, no. 23 (December 2, 2022): 5971–86. http://dx.doi.org/10.5194/hess-26-5971-2022.
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Abstract. Global hydrological models have become a valuable tool for a range of global impact studies related to water resources. However, glacier parameterization is often simplistic or non-existent in global hydrological models. By contrast, global glacier models do represent complex glacier dynamics and glacier evolution, and as such, they hold the promise of better resolving glacier runoff estimates. In this study, we test the hypothesis that coupling a global glacier model with a global hydrological model leads to a more realistic glacier representation and, consequently, to improved runoff predictions in the global hydrological model. To this end, the Global Glacier Evolution Model (GloGEM) is coupled with the PCRaster GLOBal Water Balance model, version 2.0 (PCR-GLOBWB 2), using the eWaterCycle platform. For the period 2001–2012, the coupled model is evaluated against the uncoupled PCR-GLOBWB 2 in 25 large-scale (>50 000 km2), glacierized basins. The coupled model produces higher runoff estimates across all basins and throughout the melt season. In summer, the runoff differences range from 0.07 % for weakly glacier-influenced basins to 252 % for strongly glacier-influenced basins. The difference can primarily be explained by PCR-GLOBWB 2 not accounting for glacier flow and glacier mass loss, thereby causing an underestimation of glacier runoff. The coupled model performs better in reproducing basin runoff observations mostly in strongly glacier-influenced basins, which is where the coupling has the most impact. This study underlines the importance of glacier representation in global hydrological models and demonstrates the potential of coupling a global hydrological model with a global glacier model for better glacier representation and runoff predictions in glacierized basins.
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Liang, Shumin, and Richard Greene. "A high-resolution global runoff estimate based on GIS and an empirical runoff coefficient." Hydrology Research 51, no. 6 (July 24, 2020): 1238–60. http://dx.doi.org/10.2166/nh.2020.132.
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Abstract This paper reviews 110 years of global runoff estimation. By employing the method of ordinary least square regression on a sample region's runoff coefficient, an empirical formula of a runoff coefficient is calculated for China. Based on this empirical formula applied with a high-resolution grid of precipitation, runoff is calculated resulting in an equally high-resolution map of global runoff using a geographic information system (GIS). The main results are (1) the global total runoff volume is 47,884 km3, (2) the average runoff depth is 359 mm, (3) the interior drainage region's runoff volume is 1,663 km3, and (4) the average runoff depth is 58.4 mm. The results are compared with the results of the existing literature on global runoff. This study emphasizes the importance of runoff and groundwater recharge in arid and semi-arid regions where the estimation value of runoff depth is significantly increased.
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Hobeichi, Sanaa, Gab Abramowitz, Jason Evans, and Hylke E. Beck. "Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product." Hydrology and Earth System Sciences 23, no. 2 (February 13, 2019): 851–70. http://dx.doi.org/10.5194/hess-23-851-2019.
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Abstract. No synthesized global gridded runoff product, derived from multiple sources, is available, despite such a product being useful for meeting the needs of many global water initiatives. We apply an optimal weighting approach to merge runoff estimates from hydrological models constrained with observational streamflow records. The weighting method is based on the ability of the models to match observed streamflow data while accounting for error covariance between the participating products. To address the lack of observed streamflow for many regions, a dissimilarity method was applied to transfer the weights of the participating products to the ungauged basins from the closest gauged basins using dissimilarity between basins in physiographic and climatic characteristics as a proxy for distance. We perform out-of-sample tests to examine the success of the dissimilarity approach, and we confirm that the weighted product performs better than its 11 constituent products in a range of metrics. Our resulting synthesized global gridded runoff product is available at monthly timescales, and includes time-variant uncertainty, for the period 1980–2012 on a 0.5∘ grid. The synthesized global gridded runoff product broadly agrees with published runoff estimates at many river basins, and represents the seasonal runoff cycle for most of the globe well. The new product, called Linear Optimal Runoff Aggregate (LORA), is a valuable synthesis of existing runoff products and will be freely available for download on https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f9617_9854_8096_5291 (last access: 31 January 2019).
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Murray, S. J., P. N. Foster, and I. C. Prentice. "Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model." Hydrology and Earth System Sciences Discussions 7, no. 4 (July 6, 2010): 4219–51. http://dx.doi.org/10.5194/hessd-7-4219-2010.
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Abstract. Global freshwater resources are sensitive to changes in climate, land cover and population density and distribution. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model (LPX-DGVM) is a development of the Lund-Potsdam-Jena model with improved representation of fire-vegetation interactions. It allows simultaneous consideration of the effects of changes in climate, CO2 concentration, natural vegetation and fire regime shifts on the continental hydrological cycle. Here the model is assessed for its ability to simulate large-scale spatial and temporal runoff patterns, in order to test its suitability for modelling future global water resources. Comparisons are made against observations of streamflow and a composite dataset of modelled and observed runoff (1986–1995). The model captures the main features of the geographical distribution of global runoff, but tends to overestimate runoff in much of the Northern Hemisphere (where this can be largely accounted for by freshwater extractions and the unrealistic accumulation of the simulated winter snowpack in permafrost regions) and the southern tropics. Interannual variability is represented reasonably well at the large catchment scale, as are seasonal flow timings and monthly high and low flow events. Further improvements to the simulation of intra-annual runoff might be achieved via the addition of river flow routing. Overestimates of runoff in some basins could likely be corrected by the inclusion of transmission losses and direct-channel evaporation.
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Murray, S. J., P. N. Foster, and I. C. Prentice. "Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model." Hydrology and Earth System Sciences 15, no. 1 (January 13, 2011): 91–105. http://dx.doi.org/10.5194/hess-15-91-2011.
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Abstract. Global freshwater resources are sensitive to changes in climate, land cover and population density and distribution. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model is a recent development of the Lund-Potsdam-Jena model with improved representation of fire-vegetation interactions. It allows simultaneous consideration of the effects of changes in climate, CO2 concentration, natural vegetation and fire regime shifts on the continental hydrological cycle. Here the model is assessed for its ability to simulate large-scale spatial and temporal runoff patterns, in order to test its suitability for modelling future global water resources. Comparisons are made against observations of streamflow and a composite dataset of modelled and observed runoff (1986–1995) and are also evaluated against soil moisture data and the Palmer Drought Severity Index. The model captures the main features of the geographical distribution of global runoff, but tends to overestimate runoff in much of the Northern Hemisphere (where this can be somewhat accounted for by freshwater consumption and the unrealistic accumulation of the simulated winter snowpack in permafrost regions) and the southern tropics. Interannual variability is represented reasonably well at the large catchment scale, as are seasonal flow timings and monthly high and low flow events. Further improvements to the simulation of intra-annual runoff might be achieved via the addition of river flow routing. Overestimates of runoff in some basins could likely be corrected by the inclusion of transmission losses and direct-channel evaporation.
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Chai, Yuanfang, Wouter R. Berghuijs, Kim Naudts, Thomas A. J. Janssen, Yue Yao, and Han Dolman. "Using precipitation sensitivity to temperature to adjust projected global runoff." Environmental Research Letters 16, no. 12 (November 29, 2021): 124032. http://dx.doi.org/10.1088/1748-9326/ac3795.
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Abstract Climate change affects the water cycle. Despite the improved accuracy of simulations of historical temperature, precipitation and runoff in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6), the uncertainty of the future sensitivity of global runoff to temperature remains large. Here, we identify a statistical relationship at the global scale between the sensitivity of precipitation to temperature change (1979–2014) and the sensitivity of runoff to temperature change (2015–2100). We use this relation to constrain future runoff sensitivity estimates. Our statistical relationship only slightly reduces the uncertainty range of future runoff sensitivities (order 10% reduction). However, more importantly, it raises the expected global runoff sensitivity to background global warming by 36%–104% compared to estimates taken directly from the CMIP6 model ensemble. The constrained sensitivities also indicate a shift towards globally more wet conditions and less dry conditions.
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VYAZILOVA, A. E., G. V. ALEKSEEV, and N. E. KHARLANENKOVA. "IMPACT OF GLOBAL WARMING ON RIVER INFLOW TO THE ARCTIC SEAS." Meteorologiya i Gidrologiya, no. 6 (June 2022): 46–55. http://dx.doi.org/10.52002/0130-2906-2022-6-46-55.
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An impact of global warming on river runoff into the Arctic seas is discussed. River runoff is one of the main components of the Arctic freshwater balance. Annual total river runoff is determined as the sum of runoff of six rivers: the Ob, Yenisei, Lena, Kolyma, Indigirka, and Mackenzie. The indices of zonal, meridional, and general circulation were calculated to assess the effect of atmospheric circulation. Correlations between the indices and surface air temperature and precipitation in the catchment areas confirmed the most significant influence of atmospheric transport on climatic conditions in the cold season. It was stated that annual total river runoff increased during 1979-2019, but the occurrence of peak discharges was reduced.
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Zhang, Yongqiang, Hongxing Zheng, Francis H. S. Chiew, Jorge Peña Arancibia, and Xinyao Zhou. "Evaluating Regional and Global Hydrological Models against Streamflow and Evapotranspiration Measurements." Journal of Hydrometeorology 17, no. 3 (March 1, 2016): 995–1010. http://dx.doi.org/10.1175/jhm-d-15-0107.1.
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Abstract Land surface and global hydrological models are often used to characterize global water and energy fluxes and stores and to model their future trajectories. This study evaluates estimates of streamflow and evapotranspiration (ET) obtained with a priori parameterization from a land surface model [CSIRO Atmosphere Biosphere Land Exchange (CABLE)] and a global hydrological model (H08) against a global dataset of streamflow from 644 largely unregulated catchments and ET from 98 flux towers and benchmarks their performance against two lumped conceptual daily rainfall–runoff models [modèle du Génie Rural à 4 paramètres Journalier (GR4J) and a simplified version of the HYDROLOG model (SIMHYD)]. The results show that all four models perform poorly in simulating the monthly and annual runoff values, with the rainfall–runoff models outperforming both CABLE and H08. The model biases in runoff are generally reflected as a complementary opposite bias in ET. All models can generally reproduce the observed seasonal and interannual runoff variability. The correlations between the modeled and observed runoff time series are reasonable, with the rainfall–runoff models performing slightly better than CABLE and H08 at the monthly time scale and all four models performing similarly at the annual time scale. The results suggest that while the land surface and global hydrological models cannot adequately simulate the actual runoff time series and long-term average volumes, they can reasonably simulate the monthly and interannual runoff variability and trends and can therefore be reliably used for broadscale or comparative regional and global water and energy balance assessments and simulations of future trajectories. They can be improved through validating the models or calibrating some of the more sensitive and less physically based parameters.
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Peel, Murray C., and Thomas A. McMahon. "A quality-controlled global runoff data set." Nature 444, no. 7120 (December 2006): E14. http://dx.doi.org/10.1038/nature05480.
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Wu, Pan, Sihai Liang, Xu-Sheng Wang, Jeffrey M. McKenzie, and Yuqing Feng. "Climate Change Impacts on Cold Season Runoff in the Headwaters of the Yellow River Considering Frozen Ground Degradation." Water 12, no. 2 (February 22, 2020): 602. http://dx.doi.org/10.3390/w12020602.
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Climate change has effects on hydrological change in multiple aspects, particularly in the headwaters of the Yellow River (HWYR), which is widely covered by climate-sensitive frozen ground. In this study, the annual runoff was partitioned into four runoff compositions: winter baseflow, snowmelt runoff, rainy season runoff, and recession flow. In addition, the effects of global warming, precipitation change, and frozen ground degradation were considered in long-term variation analyses of the runoff compositions. The moving t-test was employed to detect change points of the hydrometeorological data series from 1961 to 2013, and flow duration curves were used to analyze daily runoff regime change in different periods. It was found that the abrupt change points of cold season runoff, such as recession flow, winter baseflow, and snowmelt runoff, are different from that of the rainy season runoff. The increase in winter baseflow and decrease in snowmelt runoff at the end of 1990s was closely related to global warming. In the 21st century, winter baseflow presented a larger relative increase compared to rainy season runoff. The correlation analyses indicate that winter baseflow and snowmelt runoff are mainly controlled by water-resource-related factors, such as rainy season runoff and the accumulated precipitation in cold season. To analyze the global warming impacts, two runoff coefficients—winter baseflow discharge rate (Rw) and direct snowmelt runoff coefficients (Rs)—were proposed, and their correlation with freezing–thawing indices were analyzed. The increase of Rw is related to the increase in the air temperature thawing index (DDT), but Rs is mainly controlled by the air temperature freezing index (DDF). Meanwhile, the direct snowmelt runoff coefficient (Rs) is significantly and positively correlated to DDF and has decreased at a rate of 0.0011/year since 1980. Under global warming, the direct snowmelt runoff (runoff increment between March to May) of the HWYR could decrease continuously in the future due to the decrease of accumulative snow in cold season and frozen ground degradation. This study provides a better understanding of the long-term runoff characteristic changes in the HWYR.
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Shevchenko, O. L., D. V. Charny, V. I. Osadchi, and A. О. Il’chenko. "GROUNDWATER RUNOFF IN THE PIVDENNYI BUH RIVER BASIN IN CONDITIONS OF GLOBAL WARMING." Geological Journal, no. 3 (October 8, 2021): 3–16. http://dx.doi.org/10.30836/igs.1025-6814.2021.3.237361.
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This paper analyses changes in the calculated values of the specific runoff of unconfined and confined groundwaters to the rivers Pivdennyi Buh (Khmilnyk town) and Zhar (a tributary of the Pivdennyi Buh; Vinnytsia and Khmelnytsky regions) by seasons and long-term stages, for a total of 38 years (1980-2017). Regularities of seasonal changes in groundwater runoff in areas with different relief and average long-term groundwater levels (0.5-1.5; 0.8-2.5 and 2.7-4.5 m) are revealed. These changes have been shown to be closely related to abnormal air temperature fluctuations. There are four stages of successive changes in the regime of groundwater and in the volume of their runoff to rivers: I. 1980-1989 (1990) — traditionally minimal winter and autumn underground runoff, moderate summer and predominant spring runoff, dominance of runoff from the area with high GWT; ІІ. 1990-1998 — growth and advantages of groundwater runoff from the area with low GWT, reduction to the long-term minimum of groundwater runoff in the area with high GWT (0.8-2.5 m); III. From 1999 to 2014 — the predominant dominance of winter runoff over spring, slow growth of groundwater runoff in a limited area of the catchment with levels of 0.8-2.5 m; high-amplitude fluctuations of runoff and GWT with the achievement of long-term maximums in the area with GWT = 2.5-4.0 m; IV. 2015-2019 — the most intense reduction of GWT, and in the upper reaches of small rivers — of underground runoff to rivers.There is a progressive decrease in the specific flow of groundwater to rivers, and consequently of their resources — primarily for the aquifers in the upper reaches of rivers with GWT 0.5-1.5 m with no pressure recharge. Aquifers of ground water fed by confined aquifers (mainly within floodplains and the first low terraces of rivers) in the studied area of the Ukrainian massif of fracture waters have greater stability of the level regime on the background of rising temperatures and decreasing precipitation (recorded by 2020) than shallow water (0.5-2.0 m) without signs of such recharge.
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Iqbal, Muhammad Mazhar, Malik Muhammad Akram, Maqsood Ahmad, Saddam Hussain, and Ghulam Usman. "REGIONAL CLIMATIC RESPONSE TO GLOBAL WARMING AND AGRICULTURE IN PAKISTAN." Big Data in Water Resources Engineering (BDWRE) 2, no. 1 (September 29, 2021): 18–23. http://dx.doi.org/10.26480/bdwre.01.2021.18.23.
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Human-induced anthropogenic variations cause a significant change in the local climate, which in turn lead to variations in different climatic regions. The effects of global warming have wide spatial variability, feedback of climate change, like, surface temperature towards precipitation, surface, and subsurface runoff are critical. As the climate, variability is critically important for nature and society, especially if it increases in amplitude and fluctuations become more persistent. However, the issues of weather surface temperature is changing, and if so, whether this has a positive or negative impact on precipitation, surface and ground runoff, and theirs distinguish response to different climate classes, are subjects of ongoing debate. The current research is mainly concerned with distinguishing the response of surface temperature on the precipitation, storm surface run off, and subsurface runoff on different climate classes over the mainland of Pakistan, for a time duration of 71 years, from 1948–2018. Here, we used monthly based two sets of GLDAS (Global Data Assimilation System) datasets i.e. GLDAS-2.0 (1948-2010) and GLDAS-2.1 (2011-2018) having the spatial resolution of 0.25°×0.25° for surface temperature, precipitation, and runoff. While, for regional based climatic classification, Köppen Grignard climate classification map was used. The spatial-temporal trend of all the involving parameters has been estimated using Mann-Kendall’s trend. Spatial-temporal variation in the precipitation, surface temperature, and runoff fluctuations have been detected in different climatic regions. We showed that annually based variability of surface temperature has positive feedback over the surface runoff over the entire region as well as different climate regions of Pakistan. Despite the declining precipitation trend, the temperature seems to be a major cause of the melting of glaciers leading to an increase in the runoff. Based on our findings of established trends and corresponding mechanistic ‘feedback’ we hypothesize that increasing temperature might risk severe water shortage and cause disastrous floods in the future. Furthermore, different climatic zoning’s surface temperature variability contributed to observed variation in the precipitation, surface, and subsurface runoff variability, which in turn contributed to the persistent droughts. Changes in surface temperature and their impact on precipitation and runoff deliver valued evidence for understanding the region’s sensitivity over the entire region in Pakistan.
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Kalugin, Andrey. "Climate Change Effects on River Flow in Eastern Europe: Arctic Rivers vs. Southern Rivers." Climate 11, no. 5 (May 9, 2023): 103. http://dx.doi.org/10.3390/cli11050103.
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The hydrological model ECOMAG was used to calculate runoff characteristics in the main arctic (Northern Dvina and Pechora) and southern (Don and Kuban) river basins of Eastern Europe using the data from the ensemble of global climate models under the scenario of 1.5 and 2 °C global warming in the 21st century relative to pre-industrial values. Flow generation models were calibrated and validated based on runoff measurements at gauging stations using meteorological observation data. According to the results of numerical experiments, the relative change in river runoff in European Russia increases from north to south and from east to west under global warming of 1.5 to 2 °C. As a result, hydrological systems in milder climate were found to be more vulnerable to climate change. The assessment of flow anomalies in European Russia under the selected climate scenarios revealed the following general features: winter runoff in arctic rivers would increase, spring melt runoff in the Northern Dvina and Don would decrease, and summer–autumn runoff in all studied rivers would decrease to varying degrees. The most negative runoff anomalies are characterized in the southwestern part of the Northern Dvina basin, the middle part of the Don basin, and the lowland part of the Kuban basin, whereas positive runoff anomalies are characterized in the northern and eastern parts of the Pechora basin. Global warming of 1.5 to 2 °C would have the greatest impact on the rate of reduction of Kuban summer–autumn runoff and Don runoff during the spring flood, as well as the increase in Northern Dvina and Pechora winter runoff.
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Liu, Bojun, Xiaohui Lei, Siyu Cai, Shaoming Peng, and Dawei Zhang. "Short-term Runoff Forecasting based on Hydrological Factors at Nanchang Section of Ganjiang River, China." MATEC Web of Conferences 246 (2018): 01025. http://dx.doi.org/10.1051/matecconf/201824601025.
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With the change of global climate and underlying surface characteristics, and increasing human activities, hydro-meteorological factors such as precipitation, evaporation, and runoff. Etc., are directly affected, therefore the assumption of stationarity may no longer exist. In a changing environment, the conventional runoff forecasting methods become invalid, which brings challenges to accurate hydrometeorological forecast. A hydrological model based on the changing environment was employed to forecast the runoff at Nanchang Section of Ganjiang River in this paper, and the rationality and validity of the built model were verified. The results shows that the built hydrological model has high accuracy in the short-term runoff forecasting, and better forecasting effect has been obtained after the parameters calibration and the real-time correction of the predicted runoffs, which can provide the strong support for the scientific water resources operation decision and also provide the boundary conditions of water level and water quality for the hydrodynamic and water-quality simulation at the Nanchang Section of the Ganjiang River.
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Arnell, N. W. "Effects of IPCC SRES* emissions scenarios on river runoff: a global perspective." Hydrology and Earth System Sciences 7, no. 5 (October 31, 2003): 619–41. http://dx.doi.org/10.5194/hess-7-619-2003.
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Abstract. This paper describes an assessment of the implications of future climate change for river runoff across the entire world, using six climate models which have been driven by the SRES emissions scenarios. Streamflow is simulated at a spatial resolution of 0.5°x0.5&#176 using a macro-scale hydrological model, and summed to produce total runoff for almost 1200 catchments. The effects of climate change have been compared with the effects of natural multi-decadal climatic variability, as determined from a long unforced climate simulation using HadCM3. By the 2020s, change in runoff due to climate change in approximately a third of the catchments is less than that due to natural variability but, by the 2080s, this falls to between 10 and 30%. The climate models produce broadly similar changes in runoff, with increases in high latitudes, east Africa and south and east Asia, and decreases in southern and eastern Europe, western Russia, north Africa and the Middle East, central and southern Africa, much of North America, most of South America, and south and east Asia. The pattern of change in runoff is largely determined by simulated change in precipitation, offset by a general increase in evaporation. There is little difference in the pattern of change between different emissions scenarios (for a given model), and only by the 2080s is there evidence that the magnitudes of change in runoff vary, with emissions scenario A1FI producing the greatest change and B1 the smallest. The inter-annual variability in runoff increases in most catchments due to climate change — even though the inter-annual variability in precipitation is not changed — and the frequency of flow below the current 10-year return period minimum annual runoff increases by a factor of three in Europe and southern Africa and of two across North America. Across most of the world climate change does not alter the timing of flows through the year but, in the marginal zone between cool and mild climates, higher temperatures mean that peak streamflow moves from spring to winter as less winter precipitation falls as snow. The spatial pattern of changes in the 10-year return period maximum monthly runoff follows changes in annual runoff. Keywords: SRES emissions scenarios, climate change impacts on runoff, multi-decadal variability, macro-scale hydrological model, drought frequency, flood frequency
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Russell, Gary L., and James R. Miller. "Global river runoff calculated from a global atmospheric general circulation model." Journal of Hydrology 117, no. 1-4 (September 1990): 241–54. http://dx.doi.org/10.1016/0022-1694(90)90095-f.
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McLaughlin, C. J., C. A. Smith, R. W. Buddemeier, J. D. Bartley, and B. A. Maxwell. "Rivers, runoff, and reefs." Global and Planetary Change 39, no. 1-2 (October 2003): 191–99. http://dx.doi.org/10.1016/s0921-8181(03)00024-9.
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van Huijgevoort, M. H. J., P. Hazenberg, H. A. J. van Lanen, A. J. Teuling, D. B. Clark, S. Folwell, S. N. Gosling, et al. "Global Multimodel Analysis of Drought in Runoff for the Second Half of the Twentieth Century." Journal of Hydrometeorology 14, no. 5 (October 1, 2013): 1535–52. http://dx.doi.org/10.1175/jhm-d-12-0186.1.
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Abstract During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on a global scale. A multimodel ensemble analysis was carried out to evaluate if 10 such large-scale models agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runoff from 10 global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.
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Liu, Yang, Puripus Soonthornnonda, Jin Li, and Erik R. Christensen. "Stormwater Runoff Characterized by GIS Determined Source Areas and Runoff Volumes." Environmental Management 47, no. 2 (December 12, 2010): 201–17. http://dx.doi.org/10.1007/s00267-010-9591-2.
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Liu, Yaling, Mohamad Hejazi, Hongyi Li, Xuesong Zhang, and Guoyong Leng. "A hydrological emulator for global applications – HE v1.0.0." Geoscientific Model Development 11, no. 3 (March 23, 2018): 1077–92. http://dx.doi.org/10.5194/gmd-11-1077-2018.
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Abstract. While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.
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Ghiggi, Gionata, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson. "GRUN: an observation-based global gridded runoff dataset from 1902 to 2014." Earth System Science Data 11, no. 4 (November 13, 2019): 1655–74. http://dx.doi.org/10.5194/essd-11-1655-2019.
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Abstract. Freshwater resources are of high societal relevance, and understanding their past variability is vital to water management in the context of ongoing climate change. This study introduces a global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. In situ streamflow observations are used to train a machine learning algorithm that predicts monthly runoff rates based on antecedent precipitation and temperature from an atmospheric reanalysis. The accuracy of this reconstruction is assessed with cross-validation and compared with an independent set of discharge observations for large river basins. The presented dataset agrees on average better with the streamflow observations than an ensemble of 13 state-of-the art global hydrological model runoff simulations. We estimate a global long-term mean runoff of 38 452 km3 yr−1 in agreement with previous assessments. The temporal coverage of the reconstruction offers an unprecedented view on large-scale features of runoff variability in regions with limited data coverage, making it an ideal candidate for large-scale hydro-climatic process studies, water resource assessments, and evaluating and refining existing hydrological models. The paper closes with example applications fostering the understanding of global freshwater dynamics, interannual variability, drought propagation and the response of runoff to atmospheric teleconnections. The GRUN dataset is available at https://doi.org/10.6084/m9.figshare.9228176 (Ghiggi et al., 2019).
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McCabe, Gregory J., and David M. Wolock. "Variability Common to Global Sea Surface Temperatures and Runoff in the Conterminous United States." Journal of Hydrometeorology 15, no. 2 (April 1, 2014): 714–25. http://dx.doi.org/10.1175/jhm-d-13-097.1.
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Abstract Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.
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Miller, James R., and Gary L. Russell. "The impact of global warming on river runoff." Journal of Geophysical Research 97, no. D3 (1992): 2757. http://dx.doi.org/10.1029/91jd01700.
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Gedney, N., P. M. Cox, R. A. Betts, O. Boucher, C. Huntingford, and P. A. Stott. "A quality-controlled global runoff data set (Reply)." Nature 444, no. 7120 (December 2006): E14—E15. http://dx.doi.org/10.1038/nature05481.
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Liu, Jianyu, Qiang Zhang, Shuyun Feng, Xihui Gu, Vijay P. Singh, and Peng Sun. "Global Attribution of Runoff Variance Across Multiple Timescales." Journal of Geophysical Research: Atmospheres 124, no. 24 (December 27, 2019): 13962–74. http://dx.doi.org/10.1029/2019jd030539.
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Ahmadi-Sani, Naser, Lida Razaghnia, and Timo Pukkala. "Effect of Land-Use Change on Runoff in Hyrcania." Land 11, no. 2 (January 31, 2022): 220. http://dx.doi.org/10.3390/land11020220.
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Population growth and human activities have resulted in drastic changes in land use in many areas of the world, including the Hyrcania region in northern Iran. Land-use changes affect the hydrological processes of water basins. This study evaluated the effect of land-use changes on runoff over 15 years in the Haraz River basin located in Hyrcania using remote sensing data and GIS analyses. The annual precipitation of the region is 66.5 cm. Two Landsat images were used to develop land-use maps for 1996 and 2011. Original image features, their principal components, and vegetation indices were used to classify the two Landsat images into different land-use categories. Runoff was predicted from precipitation, land use, and hydrological soil groups, using the SCS-CN model (the “curve number” approach). During the 15 years, 62.4% of the area remained unchanged and 37.6% had undergone a land-use change. The highest average runoffs were obtained for bare land (14.1–14.5 cm/year) and residential land (10.4–11.4 cm/year), and the lowest for dense forest (2.5–2.6 cm/year) and first-grade rangeland (2.8–3.1 cm/year). The volume of annual runoff increased by 9% during 1996–2011 due to land-use changes. Runoff was estimated at 9.4% of precipitation in 1996, and 9.6% of precipitation in 2011. Most of the increase was related to the increased area of bare land and decreased area of rangeland. The study indicated that combined use of the SCS-CN approach, remote sensing data, and GIS tools allow cost-effective runoff estimation, helping watershed management. The results on the effect of land-use change on runoff can be seen as a warning for land-use managers and policymakers, who should aim at stopping and reversing the current land-use trends of the Haraz River basin.
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Siksnāne, Ieva, and Ainis Lagzdiņš. "Analysis of Precipitation and Runoff Conditions in Agricultural Runoff Monitoring Sites." Rural Sustainability Research 39, no. 334 (August 1, 2018): 26–31. http://dx.doi.org/10.2478/plua-2018-0004.
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Abstract In order to assess the nature of climate change, it is important to analyze the indicators of climate variability in different scales: spatial and temporal. The analysis at different scales can lead to understanding of the nature of variations. Climate change studies are essential for comprehending the nature of global processes, to refine global climate patterns and also develop further research for natural processes (Meinke, Stone, 2005; Hulme et al., 1999). Processes in nature are united, continuous and in constant interaction. Variance of interaction types are immeasurable, types can be connected with different scales and science fields, for example, biological, ecological, physical etc. If interaction is taking place between the land and atmosphere, it is defined as hydrological interaction. As water is significantly important for many purposes on the Earth, it is relevant to analyze precipitation and water runoff on a local scale. In the territory of Latvia, the amount of precipitation exceeds the level of evapotranspiration. Long-term monitoring data show that precipitation leads to average runoff of 250 mm per year (Ziverts, 2004). The monitoring data collected at three research sites located in Latvia was used for this research including Berze (Lielupe river basin, meteorological station in Dobele), Mellupite (Venta river basin, meteorological station in Saldus monitoring) and Vienziemite (Gauja river basin, meteorological station in Zoseni). The results from this study show that there is a pronounced interaction between runoff and precipitation with an average of 53 to 82%.
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Chen, Lei, Jianxia Chang, Yimin Wang, and Yuelu Zhu. "Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios." Hydrology Research 50, no. 1 (July 5, 2018): 24–42. http://dx.doi.org/10.2166/nh.2018.192.
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Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.
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van Huijgevoort, M. H. J., P. Hazenberg, H. A. J. van Lanen, and R. Uijlenhoet. "A generic method for hydrological drought identification across different climate regions." Hydrology and Earth System Sciences 16, no. 8 (August 3, 2012): 2437–51. http://dx.doi.org/10.5194/hess-16-2437-2012.
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Abstract. The identification of hydrological drought at global scale has received considerable attention during the last decade. However, climate-induced variation in runoff across the world makes such analyses rather complicated. This especially holds for the drier regions of the world (both cold and warm), where, for a considerable period of time, zero runoff can be observed. In the current paper, we present a method that enables to identify drought at global scale across climate regimes in a consistent manner. The method combines the characteristics of the classical variable threshold level method that is best applicable in regions with non-zero runoff most of the time, and the consecutive dry days (period) method that is better suited for areas where zero runoff occurs. The newly presented method allows a drought in periods with runoff to continue in the following period without runoff. The method is demonstrated by identifying droughts from discharge observations of four rivers situated within different climate regimes, as well as from simulated runoff data at global scale obtained from an ensemble of five different land surface models. The identified drought events obtained by the new approach are compared to those resulting from application of the variable threshold level method or the consecutive dry period method separately. Results show that, in general, for drier regions, the threshold level method overestimates drought duration, because zero runoff periods are included in a drought, according to the definition used within this method. The consecutive dry period method underestimates drought occurrence, since it cannot identify droughts for periods with runoff. The developed method especially shows its relevance in transitional areas, because, in wetter regions, results are identical to the classical threshold level method. By combining both methods, the new method is able to identify single drought events that occur during positive and zero runoff periods, leading to a more realistic global drought characterization, especially within drier environments.
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van Huijgevoort, M. H. J., P. Hazenberg, H. A. J. van Lanen, and R. Uijlenhoet. "A generic method for hydrological drought identification across different climate regions." Hydrology and Earth System Sciences Discussions 9, no. 2 (February 16, 2012): 2033–70. http://dx.doi.org/10.5194/hessd-9-2033-2012.
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Abstract. The identification of hydrological drought at global scale has received considerable attention during the last decade. However, climate-induced variation in runoff across the world makes such analyses rather complicated. This especially holds for the drier regions of the world (both cold and warm), where for a considerable period of time, zero runoff can be observed. In the current paper, we present a method that enables to identify drought at global scale across climate regimes in a consistent manner. The method combines the characteristics of the classical variable threshold level method that is best applicable in regions with non zero runoff most of the time, and the consecutive dry days (period) method that is better suited for areas where zero runoff occurs. The newly presented method allows a drought in periods with runoff to continue in the following period without runoff. The method was demonstrated by identifying droughts from discharge observations of four rivers situated within different climate regimes, as well as from simulated runoff data at global scale obtained from an ensemble of five different land surface models. The identified drought events obtained by the new approach were compared to those resulting from application of the variable threshold level method or the consecutive dry period method separately. Results show that, in general, for drier regions, the threshold level method overestimates drought duration, because zero runoff periods were included in a drought, according to the definition used within this method. The consecutive dry period method underestimates drought occurrence, since it cannot identify droughts for periods with runoff. The developed method especially shows its relevance in transitional areas, because in wetter regions, results were identical to the classical threshold level method. By combining both methods, the new method is able to identify single drought events that occur during positive and zero runoff periods, leading to a more realistic global drought characterization, especially within drier environments.
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Klimenko, V. V., and E. V. Fedotova. "Russian hydropower under the global climate change." Доклады Академии наук 484, no. 2 (April 13, 2019): 156–60. http://dx.doi.org/10.31857/s0869-56524842156-160.
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The influence of the climate change in Russia on the operation of hydroelectric power plants during the 21st century is considered. For obtaining quantitative assessments, the results yielded by global climatic models for river runoff were subjected to ensemble averaging. In addition to the standard RCP climatic scenarios, the MPEI scenario is considered, the fundamental distinctive feature of which is that the most likely development trajectories are selected. It is found that the choice of a scenario has an essential effect on both the qualitative pattern of river runoff changes over the territory and on the quantitative characteristics of this process.An integral assessment for the change in the hydroelectric power plant outputs due to climate change is made.
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Giuntoli, I., J. P. Vidal, C. Prudhomme, and D. M. Hannah. "Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models." Earth System Dynamics 6, no. 1 (May 18, 2015): 267–85. http://dx.doi.org/10.5194/esd-6-267-2015.
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Abstract. Projections of changes in the hydrological cycle from global hydrological models (GHMs) driven by global climate models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow-dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs' precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the need for improvements in modelling snowmelt and runoff processes to project future hydrological extremes and the importance of using multiple GCMs and GHMs to encompass the uncertainty range provided by these two sources.
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Giuntoli, I., J. P. Vidal, C. Prudhomme, and D. M. Hannah. "Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models." Earth System Dynamics Discussions 6, no. 1 (January 6, 2015): 1–30. http://dx.doi.org/10.5194/esdd-6-1-2015.
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Abstract. Projections of changes in the hydrological cycle from Global Hydrological Models (GHMs) driven by Global Climate Models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using 6 GHMs and 5 GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a 2-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the importance of using multiple GCMs and GHMs to envelope the overall uncertainty range and the need for improvements in modeling snowmelt and runoff processes to project future hydrological extremes.
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Surfleet, Christopher G., Arne E. Skaugset, and Matthew W. Meadows. "Road runoff and sediment sampling for determining road sediment yield at the watershed scale." Canadian Journal of Forest Research 41, no. 10 (October 2011): 1970–80. http://dx.doi.org/10.1139/x11-104.
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In this study, we demonstrate that watershed-scale estimates of road sediment production are improved if field measurements of road runoff and sediment production are used in the analysis. We used several techniques to spatially extrapolate measurements of road runoff and sampled sediment: comprehensive road runoff measurements, runoff estimates derived from the Distributed Hydrology Soil Vegetation Model (DHSVM), and adjustment of the road erosion models WARSEM and SEDMODL2.The sediment yield for the Oak Creek, Oregon, road network based on measured road runoff and sediment was 6.5 tons/year. When DHSVM was used to simulate road runoff, the estimated sediment from roads was similar, 6.9 tons/years. The road sediment production estimated by SEDMODL2 and WARSEM, adjusted with field-measured road runoff and sediment, was 28% and 34% less, respectively, than using the models with the default parameters. When applied to a road network in commercial forest land with frequent road use, the sediment yield estimated by SEDMODL2 and WARSEM without adjustment from field measurements was 480% and 610% higher, respectively, than with adjustments. We found that measuring runoff and sediment from one large storm event (≥1 year recurrence) provided a statistically significant relationship with the annual sediment yield.
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Kalugin, Andrey. "Hydrological and Meteorological Variability in the Volga River Basin under Global Warming by 1.5 and 2 Degrees." Climate 10, no. 7 (July 15, 2022): 107. http://dx.doi.org/10.3390/cli10070107.
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The idea of the research to assess the impact of 1.5 °C and 2 °C global warming in the 21st century on the runoff formation in the Volga basin corresponds to the Paris agreement on climate change 2016 with the main goal to keep the global air temperature rise to below 2 °C relative to the pre-industrial level and to take measures to limit warming to 1.5 °C by the end of the 21st century. The purpose of this study was to obtain physically based results of changes in the water regime of the Volga basin rivers under global warming by 1.5 °C and 2 °C relative to pre-industrial values. The physical and mathematical model of runoff generation ECOMAG (ECOlogical Model for Applied Geophysics) was applied in calculations using data from global climate models (GCMs). The estimation of flow anomalies of the Volga River and its major tributaries showed a decrease in annual runoff by 10–11% relative to the period from 1970 to 1999. The largest relative decrease in runoff by 17–20% was noted for the Oka and Upper Volga rivers, while the Kama River had only a 1–5% decrease. The Volga winter runoff increased by 17% and 28% under global warming by 1.5 °C and 2 °C, respectively, and negative runoff anomalies during the spring flood and the summer–autumn period turned out to be in the range of 21 to 23%. Despite the increase in precipitation, the role of evaporation in the water balance of the Volga basin will only increase.
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Lorenz, Christof, Harald Kunstmann, Balaji Devaraju, Mohammad J. Tourian, Nico Sneeuw, and Johannes Riegger. "Large-Scale Runoff from Landmasses: A Global Assessment of the Closure of the Hydrological and Atmospheric Water Balances*." Journal of Hydrometeorology 15, no. 6 (December 1, 2014): 2111–39. http://dx.doi.org/10.1175/jhm-d-13-0157.1.
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Abstract The performance of hydrological and hydrometeorological water-balance-based methods to estimate monthly runoff is analyzed. Such an analysis also allows for the examination of the closure of water budgets at different spatial (continental and catchment) and temporal (monthly, seasonal, and annual) scales. For this analysis, different combinations of gridded observations [Global Precipitation Climatology Centre (GPCC), Global Precipitation Climatology Project (GPCP), Climate Prediction Center (CPC), Climatic Research Unit (CRU), and University of Delaware (DEL)], atmospheric reanalysis models [Interim ECMWF Re-Analysis (ERA-Interim), Climate Forecast System Reanalysis (CFSR), and Modern-Era Retrospective Analysis for Research and Applications (MERRA)], partially model-based datasets [Global Land Surface Evaporation: The Amsterdam Methodology (GLEAM), Moderate Resolution Imaging Spectroradiometer (MODIS) Global Evapotranspiration Project (MOD16), and FLUXNET Multi-Tree Ensemble (FLUXNET MTE)], and Gravity Recovery and Climate Experiment (GRACE) satellite-derived water storage changes are employed. The derived ensemble of hydrological and hydrometeorological budget–based runoff estimates, together with results from different land surface hydrological models [Global Land Data Assimilation System (GLDAS) and the land-only version of MERRA (MERRA-Land)] and a simple predictor based on the precipitation–runoff ratio, is compared with observed monthly in situ runoff for 96 catchments of different sizes and climatic conditions worldwide. Despite significant shortcomings of the budget-based methods over many catchments, the evaluation allows for the demarcation of areas with consistently reasonable runoff estimates. Good agreement was particularly observed when runoff followed a dominant annual cycle like the Amazon. This holds true also for catchments with an area far below the spatial resolution of GRACE, like the Rhine. Over catchments with low or nearly constant runoff, the budget-based approaches do not provide realistic runoff estimates because of significant biases in the input datasets. In general, no specific data combination could be identified that consistently performed over all catchments. Thus, the performance over a specific single catchment cannot be extrapolated to other regions. Only in few cases do specific dataset combinations provide reasonable water budget closure; in most cases, significant imbalances remain for all the applied datasets.
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Zhang, Qifei, Yaning Chen, Zhi Li, Gonghuan Fang, Yanyun Xiang, Yupeng Li, and Huiping Ji. "Recent Changes in Water Discharge in Snow and Glacier Melt-Dominated Rivers in the Tienshan Mountains, Central Asia." Remote Sensing 12, no. 17 (August 20, 2020): 2704. http://dx.doi.org/10.3390/rs12172704.
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Global warming has generally led to changes in river runoffs fed by snow and glacier meltwater in mountain ranges. The runoff of the Aksu River, which originates in the Southern Tienshan Mountains, exhibited a positive trend during 1979–2002, but this trend reversed during 2002–2015. Through a comprehensive analysis, this study aims to estimate potential reasons for changes in the runoff of its two contrasting headwaters: the Toxkan and Kumalak Rivers, based on climatic data, the altitude of the 0 °C isotherm, glacier mass balance (GMB), snow cover area (SCA), snow depth (SD) and the sensitivity model. For the Toxkan River, the decrease in spring runoff mainly resulted from reductions in precipitation, whereas the decrease in summer runoff was mainly caused by early snowmelt in spring and a much-reduced snow meltwater supply in summer. In addition, the obvious glacier area reduction in the catchment (decreased to less than 4%) also contributed to the reduced summer runoff. For the Kumalak River, a sharp decrease rate of 10.21 × 108 m3/decade in runoff was detected due to summertime cooling of both surface and upper air temperatures. Reduced summer temperatures with a positive trend in precipitation not only inhibited glacier melting but also dropped the 0 °C layer altitude, resulting in a significant increase in summertime SCA and SD, a slowing of the glacier negative mass balance, and a lowering of the snow-line altitude.
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Sishah, Shimelis. "Rainfall runoff estimation using GIS and SCS-CN method for awash river basin, Ethiopia." International Journal of Hydrology 5, no. 1 (March 22, 2021): 33–37. http://dx.doi.org/10.15406/ijh.2021.05.00263.
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Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.
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Weiland, F. C. Sperna, L. P. H. van Beek, J. C. J. Kwadijk, and M. F. P. Bierkens. "On the Suitability of GCM Runoff Fields for River Discharge Modeling: A Case Study Using Model Output from HadGEM2 and ECHAM5." Journal of Hydrometeorology 13, no. 1 (February 1, 2012): 140–54. http://dx.doi.org/10.1175/jhm-d-10-05011.1.
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Abstract The representation of hydrological processes in land surface schemes (LSSs) has recently been improved. In this study, the usability of GCM runoff for river discharge modeling is evaluated by validating the mean, timing, and amplitude of the modeled annual discharge cycles against observations. River discharge was calculated for six large rivers using runoff, precipitation, and actual evaporation from the GCMs ECHAM5 and Hadley Centre Global Environmental Model version 2 (HadGEM2). Four methods were applied: 1) accumulation of GCM runoff, 2) routing of GCM runoff, 3) routing of GCM runoff combined with temporal storage of subsurface runoff, and 4) offline hydrological modeling with the global distributed hydrological model PCRaster Global Water Balance (PCR-GLOBWB) using meteorological data from the GCMs as forcing. The quality of discharge generated by all four methods is highly influenced by the quality of the GCM data. In small catchments, the methods that include runoff routing perform equally well, although offline modeling with PRC-GLOBWB outperforms the other methods for ECHAM5 data. For larger catchments, routing introduces realistic travel times, decreased day-to-day variability, and it reduces extremes. Complexity of the LSS of both GCMs is comparable to the complexity of the hydrological model. However, in HadGEM2 the absence of subgrid variability for saturated hydraulic conductivity results in a large subsurface runoff flux and a low seasonal variability in the annual discharge cycle. The analysis of these two GCMs shows that when LSSs are tuned to reproduce realistic water partitioning at the grid scale and a routing scheme is also included, discharge variability and change derived from GCM runoff could be as useful as changes derived from runoff obtained from offline simulations using large-scale hydrological models.
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Viviroli, D., and R. Weingartner. "The hydrological significance of mountains: from regional to global scale." Hydrology and Earth System Sciences 8, no. 6 (December 31, 2004): 1017–30. http://dx.doi.org/10.5194/hess-8-1017-2004.
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Abstract. Mountain regions supply a large share of the world’s population with fresh water. Quantification of the hydrological significance of mountains, however, is subject to great uncertainty. Instead of focusing on global averages in advance, the present analysis follows a catchment-based approach using discharge data provided by the Global Runoff Data Centre (GRDC). The River Rhine originating in the European Alps is chosen as a first study area, revealing the hydrological relationship between mountainous and lowland regions in a well-documented area. Following the findings from this analysis, different aspects of runoff characteristics for a total of 22 case-study river basins world-wide have been investigated and compared, for a global view. The view has been extended through aspects of climate and human use of mountain runoff. The particular hydrological characteristics of mountain areas are characterised by disproportionately large discharges. In humid areas, mountains supply up to 20–50% of total discharge while in arid areas, mountains contribute from 50–90% of total discharge, with extremes of over 95%. The overall assessment of the hydrological significance of mountain areas reveals that the world’s major "water towers" are found in arid or semi-arid zones where they provide essential fresh water for a significant proportion of a quickly growing global population. Keywords: mountain hydrology, global comparative assessment, runoff, water resources, sustainability, Rhine River, European Alps
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Lucey, Joseph T. D., John T. Reager, and Sonya R. Lopez. "Global partitioning of runoff generation mechanisms using remote sensing data." Hydrology and Earth System Sciences 24, no. 3 (March 27, 2020): 1415–27. http://dx.doi.org/10.5194/hess-24-1415-2020.
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Abstract. A set of complex processes contribute to generate river runoff, which in the hydrological sciences are typically divided into two major categories: surface runoff, sometimes called Hortonian flow, and baseflow-driven runoff or Dunne flow. In this study, we examine the covariance of global satellite-based surface water inundation (SWI) observations with two remotely sensed hydrological variables, precipitation, and terrestrial water storage, to better understand how apparent runoff generation responds to these two dominant forcing mechanisms in different regions of the world. Terrestrial water storage observations come from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, while precipitation comes from the Global Precipitation Climatology Project (GPCP) combined product, and surface inundation levels from the NASA Surface WAter Microwave Product Series (SWAMPS) product. We evaluate the statistical relationship between surface water inundation, total water storage anomalies (TWS; TWSAs), and precipitation values under different time lag and quality control adjustments between the data products. We find that the global estimation of surface inundation improves when considering a quality control threshold of 50 % reliability for the SWAMPS data and after applying time lags ranging from 1 to 5 months. Precipitation and total water storage equally control the majority of surface inundation developments across the globe. The model tends to underestimate and overestimate at locations with high interannual variability and with low inundation measurements, respectively.
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Gosling, Simon N., Dan Bretherton, Keith Haines, and Nigel W. Arnell. "Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1926 (September 13, 2010): 4005–21. http://dx.doi.org/10.1098/rsta.2010.0164.
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Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.
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Seyyedi, H., E. N. Anagnostou, E. Beighley, and J. McCollum. "Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications." Hydrology and Earth System Sciences Discussions 11, no. 7 (July 31, 2014): 9067–112. http://dx.doi.org/10.5194/hessd-11-9067-2014.
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Abstract. Deriving flood hazard maps for ungauged basins typically requires simulating a long record of annual maximum discharges. To improve this approach, precipitation from global reanalysis systems must be downscaled to a spatial and temporal resolution applicable for flood modeling. This study evaluates such downscaling and error correction approaches for improving hydrologic applications using a combination of NASA's Global Land Data Assimilation System (GLDAS) precipitation dataset and a higher resolution multi-satellite precipitation product (TRMM). The study focuses on 437 flood-inducing storm events that occurred over a period of ten years (2002–2011) in the Susquehanna River basin located in the northeast US. A validation strategy was devised for assessing error metrics in rainfall and simulated runoff as function of basin area, storm severity and season. The WSR-88D gauge-adjusted radar-rainfall (stage IV) product was used as the reference rainfall dataset, while runoff simulations forced with the stage IV precipitation dataset were considered as the runoff reference. Results show that the generated rainfall ensembles from the downscaled reanalysis products encapsulate the reference rainfall. The statistical analysis, including frequency and quantile plots plus mean relative error and root mean square error statistics, demonstrated improvements in the precipitation and runoff simulation error statistics of the satellite-driven downscaled reanalysis dataset compared to the original reanalysis precipitation product. Results vary by season and less by basin scale. In the fall season specifically, the downscaled product has three times lower mean relative error than the original product; this ratio increases to four times for the simulated runoff values. The proposed downscaling scheme is modular in design and can be applied on gridded satellite and reanalysis dataset.
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Alkama, R., B. Decharme, H. Douville, and A. Ribes. "Trends in Global and Basin-Scale Runoff over the Late Twentieth Century: Methodological Issues and Sources of Uncertainty." Journal of Climate 24, no. 12 (June 15, 2011): 3000–3014. http://dx.doi.org/10.1175/2010jcli3921.1.
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Abstract While human influence has been detected in global and regional surface air temperature, detection–attribution studies of direct (i.e., land use and water management) and indirect (i.e., climate related) effects of human activities on land surface hydrology remain a crucial and controversial issue. In the present study, a set of global offline hydrological simulations is performed during the 1960–94 period using the Interactions between Soil, Biosphere, and Atmosphere–Total Runoff Integrating Pathways (ISBA-TRIP) modeling system. In contrast to previous numerical sensitivity studies, the model captures the observed trend in river runoff over most continents without including land use changes and/or biophysical CO2 effects, at least when the comparison is made over 154 large rivers with a minimum amount of missing data. The main exception is northern Asia, where the simulated runoff trend is negative, in line with the prescribed precipitation forcing but in contrast with the observed runoff trend. The authors hypothesize that the observed surface warming and the associated decline of permafrost and glaciers, not yet included in most land surface models, could have contributed to the increased runoff at high latitudes. They also emphasize that the runoff trend is a regional-scale issue, if not basin dependent. In line with recent observational studies, their results suggest that CO2 stomatal conductance effects and land use changes are not the primary drivers of the multidecadal runoff variability at continental scales. However, the authors do not rule out a human influence on land runoff, at least through the high-latitude surface warming observed over recent decades.
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Gosling, S. N., R. G. Taylor, N. W. Arnell, and M. C. Todd. "A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models." Hydrology and Earth System Sciences Discussions 7, no. 5 (September 23, 2010): 7191–229. http://dx.doi.org/10.5194/hessd-7-7191-2010.
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Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.