scholarly journals A Modified ABCD Model with Temperature-Dependent Parameters for Cold Regions: Application to Reconstruct the Changing Runoff in the Headwater Catchment of the Golmud River, China

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1812
Author(s):  
Xiaoshu Wang ◽  
Bing Gao ◽  
Xusheng Wang
Keyword(s):  
Groundwater Level ◽  
Hydrological Model ◽  
Cold Season ◽  
Annual Runoff ◽  
Frozen Soil ◽  
Washington Dc ◽  
Temperature Dependent ◽  
Cold Regions ◽  
Monthly Runoff ◽  
Headwater Catchment

The runoff changes due to global warming in hydrological basins in the Qinghai–Tibetan Plateau (QTP) have received worldwide attention. The headwater catchment of the Golmud River, located in the northern QTP, is the main source of water resources for the Golmud city in an arid region but has been poorly known for the hydroclimatological behaviors. In this study, a widely-used hydrological model, the ABCD model (Thomas, H.A., Washington, DC, USA), is modified by incorporating temperature-dependent hydrological processes and groundwater evapotranspiration in cold regions with a few additional parameters. The new model is used to reconstruct the monthly runoff in the past decades for the headwater catchment of the Golmud River and performs better than other comparable models. As indicated, the annual snowmelt runoff increased with the increasing air temperature and became more concentrated in April than in May. The frozen soil degradation could increase the hydraulic conductivity of soils and lead to a rise in cold season runoff. The groundwater level in the Golmud city was positively correlated to the annual runoff in the headwater catchment of the Golmud River, indicating that an increase of the groundwater level could be triggered by the rising trend in the streamflow of the Golmud River. This study suggests a useful hydrological model for the groundwater management in the Golmud city.

scholarly journals A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

2010 ◽  
Vol 7 (5) ◽  
pp. 7191-7229 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Model ◽  
Annual Runoff ◽  
Structural Uncertainty ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Monthly Runoff ◽  
Global Mean ◽  
Impacts Of Climate Change

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.

scholarly journals A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

2011 ◽  
Vol 15 (1) ◽  
pp. 279-294 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Model ◽  
Annual Runoff ◽  
Structural Uncertainty ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Monthly Runoff ◽  
Global Mean ◽  
Impacts Of Climate Change

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). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. 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 (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), 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 (Mac-PDM.09 here) 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.

scholarly journals Integrated assessment of climate and human contributions to variations in streamflow in the Ten Great Gullies Basin of the Upper Yellow River, China

2020 ◽  
Vol 68 (3) ◽  
pp. 249-259
Author(s):  
Tong Liu ◽  
He Qing Huang ◽  
Ming an Shao ◽  
Jiong Cheng ◽  
Xiang Dong Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Hydrological Model ◽  
Yellow River ◽  
Annual Runoff ◽  
Integrated Method ◽  
Climate Elasticity ◽  
Relative Contribution ◽  
Pettitt Test ◽  
Monthly Runoff

AbstractClimate change and human activity are two linked factors that alter the spatiotemporal distribution of the available water. Assessing the relative contribution of the two factors on runoff changes can help the planners and managers to better formulate strategies and policies regarding regional water resources. In this work, using two typical sub-basins of the Yellow River as the study area, we first detected the trend and the breakpoint in the annual streamflow data with the Pettitt test during the period 1964–2011. Next, a Budyko-based climate elasticity model and a monthly hydrological model were employed as an integrated method to distinguish the relative contributions of climate change and human activities to the long-term changes in runoff. The results showed that a significant decline in the annual runoff occurred in the two sub-basins during the study period, and the abrupt change point in the annual runoff at the two sub-basins both occurred in 1997. The conceptual hydrological model performed well in reproducing monthly runoff time series at the two sub-basins. The Nash-Sutcliffe efficiency (NSE) between observed and simulated runoff during the validation period exceeds 0.83 for the two sub-basins. Climate elasticity method and hydrological model give consistent attribution results: human activities are the major drivers responsible for the decreased annual runoff in the Ten Great Gullies Basin. The relative contributions of climate change and human activities to the changes in the annual runoff were 22–32% and 68–78%, respectively.

scholarly journals Simulating cold-region hydrology in an intensively drained agricultural watershed in Manitoba, Canada, using the Cold Regions Hydrological Model

2017 ◽  
Vol 21 (7) ◽  
pp. 3483-3506 ◽  
Author(s):  
Marcos R. C. Cordeiro ◽  
Henry F. Wilson ◽  
Jason Vanrobaeys ◽  
John W. Pomeroy ◽  
Xing Fang ◽  
...  
Keyword(s):  
Preferential Flow ◽  
Model Development ◽  
Agricultural Watershed ◽  
Frozen Soil ◽  
Red River ◽  
Hydrological Processes ◽  
Low Flow ◽  
Northern Great Plains ◽  
Agricultural Watersheds ◽  
Cold Regions

Abstract. Etrophication and flooding are perennial problems in agricultural watersheds of the northern Great Plains. A high proportion of annual runoff and nutrient transport occurs with snowmelt in this region. Extensive surface drainage modification, frozen soils, and frequent backwater or ice-damming impacts on flow measurement represent unique challenges to accurately modelling watershed-scale hydrological processes. A physically based, non-calibrated model created using the Cold Regions Hydrological Modelling platform (CRHM) was parameterized to simulate hydrological processes within a low slope, clay soil, and intensively surface drained agricultural watershed. These characteristics are common to most tributaries of the Red River of the north. Analysis of the observed water level records for the study watershed (La Salle River) indicates that ice cover and backwater issues at time of peak flow may impact the accuracy of both modelled and measured streamflows, highlighting the value of evaluating a non-calibrated model in this environment. Simulations best matched the streamflow record in years when peak and annual discharges were equal to or above the medians of 6.7 m3 s−1 and 1.25  × 107 m3, respectively, with an average Nash–Sutcliffe efficiency (NSE) of 0.76. Simulation of low-flow years (below the medians) was more challenging (average NSE  <  0), with simulated discharge overestimated by 90 % on average. This result indicates the need for improved understanding of hydrological response in the watershed under drier conditions. Simulation during dry years was improved when infiltration was allowed prior to soil thaw, indicating the potential importance of preferential flow. Representation of in-channel dynamics and travel time under the flooded or ice-jam conditions should also receive attention in further model development efforts. Despite the complexities of the study watershed, simulations of flow for average to high-flow years and other components of the water balance were robust (snow water equivalency (SWE) and soil moisture). A sensitivity analysis of the flow routing model suggests a need for improved understanding of watershed functions under both dry and flooded conditions due to dynamic routing conditions, but overall CRHM is appropriate for simulation of hydrological processes in agricultural watersheds of the Red River. Falsifications of snow sublimation, snow transport, and infiltration to frozen soil processes in the validated base model indicate that these processes were very influential in stream discharge generation.

Effects of frozen soil and snow cover on cold-season soil water dynamics in Tokachi, Japan

2010 ◽  
Vol 24 (13) ◽  
pp. 1755-1765 ◽  
Author(s):  
Yukiyoshi Iwata ◽  
Tomoyoshi Hirota ◽  
Masaki Hayashi ◽  
Shinji Suzuki ◽  
Shuichi Hasegawa
Keyword(s):  
Snow Cover ◽  
Soil Water ◽  
Cold Season ◽  
Frozen Soil ◽  
Water Dynamics ◽  
Soil Water Dynamics

scholarly journals Frozen soil parameterization in a distributed biosphere hydrological model

2009 ◽  
Vol 6 (6) ◽  
pp. 6895-6928
Author(s):  
L. Wang ◽  
T. Koike ◽  
K. Yang ◽  
R. Jin ◽  
H. Li
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Model ◽  
Frozen Soil ◽  
Surface Radiation ◽  
Moisture Profile ◽  
Flood Peak ◽  
Radiation Fluxes ◽  
Soil Moisture Profile ◽  
The Web

Abstract. In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). In the summer 2008, land surface parameters were optimized using the observed surface radiation fluxes and the soil temperature profile at the Dadongshu-Yakou (DY) station in July; and then soil hydraulic parameters were obtained by the calibration of the July soil moisture profile at the DY station and by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak of 2008. The calibrated WEB-DHM with the frozen scheme was then used for a yearlong simulation from 21 November 2007 to 20 November 2008, to check its performance in cold seasons. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the DY station and the discharges at the basin outlet in the yearlong simulation.

scholarly journals Magnetic resonance sounding measurements as posterior information to condition hydrological model parameters: Application to a hard-rock headwater catchment

2020 ◽  
Vol 587 ◽  
pp. 124941 ◽  
Author(s):  
Nolwenn Lesparre ◽  
Jean-François Girard ◽  
Benjamin Jeannot ◽  
Sylvain Weill ◽  
Marc Dumont ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Hydrological Model ◽  
Hard Rock ◽  
Model Parameters ◽  
Magnetic Resonance Sounding ◽  
Headwater Catchment

scholarly journals Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Monthly Runoff

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.

Roles of clay layers in rainfall-runoff processes in a serpentinite headwater catchment

2020 ◽  
Author(s):  
Takahiko Yoshino ◽  
Shin'ya Katsura
Keyword(s):  
Water Flow ◽  
Groundwater Level ◽  
Mineral Soil ◽  
High Water ◽  
Organic Soil ◽  
Rainfall Runoff ◽  
Soil Layers ◽  
Clay Layers ◽  
Headwater Catchment

&lt;p&gt;Rainfall-runoff processes in a headwater catchment have been typically explained by water flow in permeable soil layers (comprised of organic soil layers and mineral soil layers produced by weathering of bedrock) overlying less permeable layers (i.e., bedrock). In a catchment where mineral soils are characterized by clayey materials (e.g., mudstone, slate, and serpentine catchment), it is possible that mineral soil layers function substantially as less permeable layers because of a low permeability of clayey materials. However, roles of clay layers in rainfall-runoff processes in such a headwater catchment are not fully understood. In this study, we conducted detailed hydrological, hydrochemical, and thermal observations in a serpentinite headwater catchment (2.12 ha) in Hokkaido, Northern Japan, where mineral soil layers consisting of thick clay layers (thickness: approximately 1.5 m) produced by weathering of the serpentinite bedrock underlies organic soil layers (thickness: approximately 0.4 m). Saturated hydraulic conductivity (Ks) and water retention curve of these two layers were also measured in a laboratory. The observation results demonstrated that groundwater was formed perennially in the organic soil layers and clay layers. The groundwater level within the organic soil layers and specific discharge of the catchment showed rapid and flashy change in response to rainfall. In contrast, the groundwater level within the clay layers showed slow and small change. Temperature of the groundwater and stream water suggested that water from the depth of the organic soil layers contributed to streamflow. The electric conductivity (EC) of the groundwater in the clay layers was very high, ranging from 321 to 380 &amp;#181;S cm&amp;#713;&amp;#185;. On the other hand, the EC of soil water (unsaturated water stored in the organic soil layers) was relatively low, ranging from 98 to 214 &amp;#181;S cm&amp;#713;&amp;#185;. Hydrograph separation using EC showed that contribution of water emerging from the clay layers to the total streamflow ranged from 31 to 76% in low to high flow periods. Temporal variation in the total head, measured using tensiometers installed at four depths at the ridge of the catchment, indicated that in wet periods when the groundwater level in the organic soil layers was high, water flow from the organic soil layers to the clay layers occurred, whereas, in dry periods, water flow from the clay layers into the organic soil layers occurred. The laboratory measurements showed that the organic soil layers had high Ks (10&amp;#713;&amp;#178; cm s&amp;#713;&amp;#185;) and low water-holding capacity, whereas the clay layers had low Ks (10&amp;#713;&amp;#8308; cm s&amp;#713;&amp;#185;) and high water-holding capacity. It can be concluded from these results that clay layers play two roles: (1) forming perched groundwater table and lateral flow on the clay layers (the role of less permeable layers) and (2) supplying water into the organic soil layers in the dry periods (the role of water supplier).&lt;/p&gt;

Climatic control on river discharge simulations, Mittivakkat Glacier catchment, Ammassalik Island, SE Greenland*

2006 ◽  
Vol 37 (4-5) ◽  
pp. 327-346 ◽  
Author(s):  
S.H. Mernild ◽  
B. Hasholt
Keyword(s):  
Time Lapse ◽  
Annual Runoff ◽  
Rainfall Runoff ◽  
Scenario Period ◽  
Climatic Control ◽  
Daily Difference ◽  
Monthly Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Annual Discharge

A lumped conceptual Rainfall–Runoff Model (the NAM model) was applied to quantify simulated intra- and inter-annual discharge from the Mittivakkat glacier catchment (18.4 km2, 78% glacier cover), Ammassalik Island, SE Greenland. Discharge simulations were performed for three periods: 1999–2004 (calibration period), 1993–1995 and 1998/1999 (validation period), and 2071–2100 (scenario period). In periods when observed winter discharges were lacking, visual observations from daily photographic time lapse were used for calibration. The timing and magnitude of simulated discharge were in general in good accordance with observed discharge (R2=0.77). However, discrepancies between simulated and observed discharge occur (maximum daily difference up to 3.4 m3 s−1, up to 11% difference between observed and simulated cumulative discharge, and model predicted river break-up 1–3 d before it actually occurs). For the period 2071–2100 future IPCC A2 and IPCC B2 climate scenarios were used as input for NAM based on HIRHAM RCM and HadCM3 AOGCM model simulations. The IPCC scenarios indicated mean maximum monthly runoff higher than 900 mm w.eq., and mean annual runoff around 3200 mm w.eq. yr−1, approximately one and a half times higher than the runoff in 1993–2004 of approximately 2000 mm w.eq. yr−1. The increasing runoff indicated an approximately three times higher negative glacier net mass balance ranging from about −750 mm w.eq. yr−1 (1961–1990) to approximately −2000 mm w.eq. yr−1 (2071–2100).

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