scholarly journals Attribution Analysis of Dry Season Runoff in the Lhasa River Using an Extended Hydrological Sensitivity Method and a Hydrological Model

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1187 ◽  
Author(s):  
Zhenhui Wu ◽  
Yadong Mei ◽  
Junhong Chen ◽  
Tiesong Hu ◽  
Weihua Xiao

In this study, a coupled water–energy balance equation at an arbitrary time scale was proposed as an extension of the Budyko hypothesis. The second mixed partial derivative was selected to represent the magnitude of the interaction. The extended hydrological sensitivity method was used to quantitatively evaluate the impacts of climate change, anthropogenic activities, and their interaction on dry season runoff in the Lhasa River. In addition, an ABCD model, which is a monthly hydrological model included a snowmelt module, was used to calculate the change in soil water and groundwater storage. The Mann–Kendall test, Spearman’s test, dynamic linear model (DLM), and Yamamoto’s method were used to identify trends and change points in hydro-climatic variables from 1956–2016. The results found that dry season runoff increased non-significantly over the last 61 years. Climate change, which caused an increase in dry season runoff, was the dominant factor, followed by anthropogenic activities and their interaction, which led to varying degrees of decrease. This study concluded that the methods tested here performed well in quantifying the relative impacts of climate change, anthropogenic activities, and their interaction on dry season runoff change.

2020 ◽  
Vol 20 (8) ◽  
pp. 2133-2155
Author(s):  
Aynalem T. Tsegaw ◽  
Marie Pontoppidan ◽  
Erle Kristvik ◽  
Knut Alfredsen ◽  
Tone M. Muthanna

Abstract. Climate change is one of the greatest threats currently facing the world's environment. In Norway, a change in climate will strongly affect the pattern, frequency, and magnitudes of stream flows. However, it is challenging to quantify to what extent the change will affect the flow patterns and floods from small rural catchments due to the unavailability or inadequacy of hydro-meteorological data for the calibration of hydrological models and due to the tailoring of methods to a small-scale level. To provide meaningful climate impact studies at the level of small catchments, it is therefore beneficial to use high-spatial- and high-temporal-resolution climate projections as input to a high-resolution hydrological model. In this study, we used such a model chain to assess the impacts of climate change on the flow patterns and frequency of floods in small ungauged rural catchments in western Norway. We used a new high-resolution regional climate projection, with improved performance regarding the precipitation distribution, and a regionalized hydrological model (distance distribution dynamics) between a reference period (1981–2011) and a future period (2070–2100). The flow-duration curves for all study catchments show more wet periods in the future than during the reference period. The results also show that in the future period, the mean annual flow increases by 16 % to 33 %. The mean annual maximum floods increase by 29 % to 38 %, and floods of 2- to 200-year return periods increase by 16 % to 43 %. The results are based on the RCP8.5 scenario from a single climate model simulation tailored to the Bergen region in western Norway, and the results should be interpreted in this context. The results should therefore be seen in consideration of other scenarios for the region to address the uncertainty. Nevertheless, the study increases our knowledge and understanding of the hydrological impacts of climate change on small catchments in the Bergen area in the western part of Norway.


2021 ◽  
Vol 121 ◽  
pp. 107013
Author(s):  
Dongxiang Xue ◽  
Junju Zhou ◽  
Xi Zhao ◽  
Chunfang Liu ◽  
Wei Wei ◽  
...  

2010 ◽  
Vol 14 (7) ◽  
pp. 1297-1308 ◽  
Author(s):  
D. G. Kingston ◽  
R. G. Taylor

Abstract. The changing availability of freshwater resources is likely to be one of the most important consequences of projected 21st century climate change for both human and natural systems. However, substantial uncertainty remains regarding the precise impacts of climate change on water resources, due in part due to uncertainty in GCM projections of climate change. Here we explore the potential impacts of climate change on freshwater resources in a humid, tropical catchment (the River Mitano) in the Upper Nile Basin of Uganda. Uncertainty associated with GCM structure and climate sensitivity is explored, as well as parameter specification within hydrological models. These aims are achieved by running pattern-scaled output from seven GCMs through a semi-distributed hydrological model of the catchment (developed using SWAT). Importantly, use of pattern-scaled GCM output allows investigation of specific thresholds of global climate change including the purported 2 °C threshold of "dangerous" climate change. In-depth analysis of results based on the HadCM3 GCM climate scenarios shows that annual river discharge first increases, then declines with rising global mean air temperature. A coincidental shift from a bimodal to unimodal discharge regime also results from a projected reduction in baseflow (groundwater discharge). Both of these changes occur after a 4 °C rise in global mean air temperature. These results are, however, highly GCM dependent, in both the magnitude and direction of change. This dependence stems primarily from projected differences in GCM scenario precipitation rather than temperature. GCM-related uncertainty is far greater than that associated with climate sensitivity or hydrological model parameterisation.


2010 ◽  
Vol 7 (5) ◽  
pp. 7191-7229 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd

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.


2020 ◽  
Author(s):  
Yanwen Wang

Net primary productivity (NPP) is an essential indicator of ecosystem function and sustainability and plays a vital role in the carbon cycle, especially in arid and semi-arid grassland ecosystems. Quantifying trends in NPP and identifying the contributing factors are important for understanding the relative impacts of climate change and human activities on grassland degradation. We quantified spatial and temporal patterns in potential NPP (NPPP) and actual NPP (NPPA) in Kyrgyzstan from 2000 to 2014 based on the Zhou Guangsheng model and MOD17A3 NPP data, respectively. By calculating the difference between NPPP and NPPA, we inferred human-induced NPP (NPPH) and thereby characterised changes in grassland NPP attributable to anthropogenic activities. We found that over the past two decades, both climatic variation and anthropogenic activities have significantly affected Kyrgyzstan’s grasslands. Grassland NPP decreased overall but patterns varied between provinces. Climate change, in particular changes in precipitation was the dominant factor driving grassland degradation in the north but human pressures also contributed. In the south however, human activities were associated with extensive areas of grassland recovery. The results provide important contextual understanding for supporting policy for grassland maintenance and restoration under climate change and intensifying human pressures.


2012 ◽  
Vol 9 (5) ◽  
pp. 6569-6614 ◽  
Author(s):  
H. Lauri ◽  
H. de Moel ◽  
P. J. Ward ◽  
T. A. Räsänen ◽  
M. Keskinen ◽  
...  

Abstract. The transboundary Mekong River is facing two on-going changes that are estimated to significantly impact its hydrology and the characteristics of its exceptional flood pulse. The rapid economic development of the riparian countries has led to massive plans for hydropower construction, and the projected climate change is expected to alter the monsoon patterns and increase temperature in the basin. The aim of this study is to assess the cumulative impact of these factors on the hydrology of the Mekong within next 20–30 yr. We downscaled output of five General Circulation Models (GCMs) that were found to perform well in the Mekong region. For the simulation of reservoir operation, we used an optimisation approach to estimate the operation of multiple reservoirs, including both existing and planned hydropower reservoirs. For hydrological assessment, we used a distributed hydrological model, VMod, with a grid resolution of 5 km × 5 km. In terms of climate change's impact to hydrology, we found a high variation in the discharge results depending on which of the GCMs is used as input. The simulated change in discharge at Kratie (Cambodia) between the baseline (1982–1992) and projected time period (2032–2042) ranges from −11% to +15% for the wet season and −10% to +13% for the dry season. Our analysis also shows that the changes in discharge due to planned reservoir operations are clearly larger than those simulated due to climate change: 25–160% higher dry season flows and 5–24% lower flood peaks in Kratie. The projected cumulative impacts follow rather closely the reservoir operation impacts, with an envelope around them induced by the different GCMs. Our results thus indicate that within the coming 20–30 yr, the operation of planned hydropower reservoirs is likely to have a larger impact on the Mekong hydrograph than the impacts of climate change, particularly during the dry season. On the other hand, climate change will increase the uncertainty of the estimated hydropower impacts. Consequently, both dam planners and dam operators should pay better attention to the cumulative impacts of climate change and reservoir operation to the aquatic ecosystems, including the multibillion-dollar Mekong fisheries.


2020 ◽  
Author(s):  
Manling Xiong

<p>The runoff in river systems has been significantly changed by climate change and land use/cover change (LUCC), while the magnitude and patterns vary because of the factors. Investigating the major factor impacting runoff variation is necessary for water resource management. In this work, five different water-energy balance models are used to analyze the cause of runoff variations; of these models, three are based on the Budyko framework and two are based on the ecohydrological conceptual framework. The approach is demonstrated using the upper-midstream of the Heihe Rivers. The results suggest LUCC is the dominant cause of runoff change in the range of 59.92% ~ 65.14%. The estimated impacts of climate change and LUCC are consistent among the five models. Cropping is the major human activity resulting in LUCC at the upper-midstream of the Heihe River. Meanwhile, the change in runoff is more sensitive to precipitation than to potential evapotranspiration. Our work summarizes five widely used water-energy balance models used to explain the impacts of climate change and LUCC on runoff, which may be of importance in explaining the mechanism of runoff change.</p>


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