Articles | Volume 22, issue 3
https://doi.org/10.5194/hess-22-1749-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-22-1749-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Mar 2018
Research article |
| 09 Mar 2018
Characterizing drought in terms of changes in the precipitation–runoff relationship: a case study of the Loess Plateau, China
Yuan Zhang
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 10085,
China
School of Earth Sciences and Resources, Chang'an University, Xi'an,
Shaanxi 710054, China
Xiaoming Feng
CORRESPONDING AUTHOR
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 10085,
China
Xiaofeng Wang
CORRESPONDING AUTHOR
School of Earth Sciences and Resources, Chang'an University, Xi'an,
Shaanxi 710054, China
Bojie Fu
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 10085,
China
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Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
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Jinxia An, Guangyao Gao, Chuan Yuan, Juan Pinos, and Bojie Fu
Hydrol. Earth Syst. Sci., 26, 3885–3900, https://doi.org/10.5194/hess-26-3885-2022, https://doi.org/10.5194/hess-26-3885-2022, 2022
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An in-depth investigation was conducted of all rainfall-partitioning components at inter- and intra-event scales for two xerophytic shrubs. Inter-event rainfall partitioning amount and percentage depended more on rainfall amount, and rainfall intensity and duration controlled intra-event rainfall-partitioning variables. One shrub has larger branch angle, small branch and smaller canopy area to produce stemflow more efficiently, and the other has larger biomass to intercept more rainfall.
Shuang Song, Shuai Wang, Xutong Wu, Yongyuan Huang, and Bojie Fu
Hydrol. Earth Syst. Sci., 26, 2035–2044, https://doi.org/10.5194/hess-26-2035-2022, https://doi.org/10.5194/hess-26-2035-2022, 2022
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Xuejing Leng, Xiaoming Feng, Bojie Fu, and Yu Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-377, https://doi.org/10.5194/hess-2021-377, 2021
Manuscript not accepted for further review
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At present, there is a lack of time series of runoff generated by glacial regions in the world. In this paper, we quantified glacial runoff (including meltwater runoff and delayed runoff) in arid regions of China from 1961 to 2015 by using remote sensing datasets of glacier mass balance with high resolution. Glacier runoff is the water resource used by oases in arid regions of China. The long-term glacial runoff data can indicate the climate risk faced by different basins in arid regions.
Yongzhe Chen, Xiaoming Feng, and Bojie Fu
Earth Syst. Sci. Data, 13, 1–31, https://doi.org/10.5194/essd-13-1-2021, https://doi.org/10.5194/essd-13-1-2021, 2021
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Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By calibrating and combining 11 different products derived from satellite observation, we developed a new global surface soil moisture dataset spanning from 2003 to 2018 with high accuracy. Using this new dataset, not only can the global long-term trends be derived, but also the seasonal variation and spatial distribution of surface soil moisture at different latitudes can be better studied.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
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Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Jianjun Zhang, Guangyao Gao, Bojie Fu, Cong Wang, Hoshin V. Gupta, Xiaoping Zhang, and Rui Li
Hydrol. Earth Syst. Sci., 24, 809–826, https://doi.org/10.5194/hess-24-809-2020, https://doi.org/10.5194/hess-24-809-2020, 2020
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We proposed an approach that integrates universal multifractals and a segmentation algorithm to precisely identify extreme precipitation (EP) and assess spatiotemporal EP variation over the Loess Plateau, using daily data. Our results explain how EP contributes to the widely distributed severe natural hazards. These findings are of great significance for ecological management in the Loess Plateau. Our approach is also helpful for spatiotemporal EP assessment at the regional scale.
Chuan Yuan, Guangyao Gao, Bojie Fu, Daming He, Xingwu Duan, and Xiaohua Wei
Hydrol. Earth Syst. Sci., 23, 4077–4095, https://doi.org/10.5194/hess-23-4077-2019, https://doi.org/10.5194/hess-23-4077-2019, 2019
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The stemflow dynamics of two xerophytic shrubs were investigated at the inter- and intra-event scales with high-temporal-resolution data in 54 rain events. Stemflow process was depicted by intensity, duration and time lags to rain events. Funneling ratio was calculated as the ratio of stemflow to rainfall intensities. Rainfall intensity and raindrop momentum controlled stemflow intensity and time lags. Influences of rainfall characteristics on stemflow variables showed temporal dependence.
Guangyao Gao, Jianjun Zhang, Yu Liu, Zheng Ning, Bojie Fu, and Murugesu Sivapalan
Hydrol. Earth Syst. Sci., 21, 4363–4378, https://doi.org/10.5194/hess-21-4363-2017, https://doi.org/10.5194/hess-21-4363-2017, 2017
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This study extracted spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield across the Loess Plateau during 1961–2011. The impacts of precipitation on sediment yield declined with time and the precipitation-sediment relationship showed a coherent spatial pattern. The sediment coefficient, representing the effect of LUCC, decreases linearly with fraction of area treated with erosion control measures and the slopes were highly variable among the catchments.
Yonggang Yang and Bojie Fu
Hydrol. Earth Syst. Sci., 21, 1757–1767, https://doi.org/10.5194/hess-21-1757-2017, https://doi.org/10.5194/hess-21-1757-2017, 2017
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This paper investigates soil water migration processes in the Loess Plateau using isotopes. The soil water migration is dominated by piston-type flow, but rarely preferential flow. Soil water from the soil lay (20–40 cm) contributed to 6–12% of plant xylem water, while soil water at the depth of 40–60 cm is the largest component (range from 60 to 66 %), soil water below 60 cm depth contributed 8–14 % to plant xylem water, and only 5–8 % is derived from precipitation.
Ji Zhou, Bojie Fu, Guangyao Gao, Yihe Lü, and Shuai Wang
Hydrol. Earth Syst. Sci., 21, 1491–1514, https://doi.org/10.5194/hess-21-1491-2017, https://doi.org/10.5194/hess-21-1491-2017, 2017
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We constructed an integrated probabilistic assessment to describe, simulate and evaluate the stochasticity of soil erosion in restoration vegetation in the Loess Plateau. We found that morphological structures in vegetation are the source of different stochasticities of soil erosion, and proved that the Poisson model is fit for predicting erosion stochasticity. This assessment could be an important complement to develop restoration strategies to improve understanding of stochasticity of erosion.
Chuan Yuan, Guangyao Gao, and Bojie Fu
Hydrol. Earth Syst. Sci., 21, 1421–1438, https://doi.org/10.5194/hess-21-1421-2017, https://doi.org/10.5194/hess-21-1421-2017, 2017
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We computed stemflow yield and efficiency, and analyzed the influential mechanism at smaller scales of leaf and raindrop. We found that precipitation was the most influential meteorological feature on stemflow. The smaller threshold precipitation to start stemflow and the more beneficial leaf traits might partly explain the larger and more efficient stemflow production. At defoliated period, the newly exposed stems replaced leaves to intercept raindrops and might really matter in stemflow yield.
N. Lu, J. Liski, R. Y. Chang, A. Akujärvi, X. Wu, T. T. Jin, Y. F. Wang, and B. J. Fu
Biogeosciences, 10, 7053–7063, https://doi.org/10.5194/bg-10-7053-2013, https://doi.org/10.5194/bg-10-7053-2013, 2013
J. Zhou, B. J. Fu, N. Lü, G. Y. Gao, Y. H. Lü, and S. Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-10083-2013, https://doi.org/10.5194/hessd-10-10083-2013, 2013
Revised manuscript not accepted
Y. D. Xu, B. J. Fu, and C. S. He
Hydrol. Earth Syst. Sci., 17, 2185–2193, https://doi.org/10.5194/hess-17-2185-2013, https://doi.org/10.5194/hess-17-2185-2013, 2013
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Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-181, https://doi.org/10.5194/hess-2024-181, 2024
Revised manuscript accepted for HESS
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small compared to large catchments, and that spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show an effect. The results can improve estimations of occurrence probabilities of extreme floods.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-211, https://doi.org/10.5194/hess-2024-211, 2024
Revised manuscript accepted for HESS
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping better prepare for and respond to floods.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
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This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-131, https://doi.org/10.5194/hess-2024-131, 2024
Revised manuscript accepted for HESS
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ET is computed from vegetation (plant transpiration) and soil (soil evaporation). In Western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented with the leaf-area-index (LAI). In this study, we evaluate the importance of LAI for the ET calculation. We take a close look at the LAI-ET interaction and show the relevance to consider both, LAI and ET. Our work contributes to the understanding of the processes of the terrestrial water cycle.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-57, https://doi.org/10.5194/hess-2024-57, 2024
Revised manuscript accepted for HESS
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. In this work we investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analysis indicate that adding two vegetation is enough to improve the representation of evaporation, and the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Cited articles
Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N.,
Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., and Hogg, E.
T.: A global overview of drought and heat-induced tree mortality reveals
emerging climate change risks for forests, Forest Ecol. Manag.,
259, 660–684, 2010.
Belal, A.-A., El-Ramady, H. R., Mohamed, E. S., and Saleh, A. M.: Drought
risk assessment using remote sensing and GIS techniques, Arab. J. Geosci., 7, 35–53, 2014.
Berg, D.: Copula goodness-of-fit testing: an overview and power comparison,
Eur. J. Financ., 15, 675–701, 2009.
Bhalme, H. N. and Mooley, D. A.: Large-Scale Droughts/Floods and Monsoon
Circulation, Mon. Weather Rev., 108, 1197–1211, 1980.
Bonan, G. B.: Forests and Climate Change: Forcings, Feedbacks, and the
Climate Benefits of Forests, Science, 320, 1444–1449, 2008.
Bouwer, L. M., Aerts, J. C. J. H., Droogers, P., and Dolman, A. J.: Detecting
the long-term impacts from climate variability and increasing water
consumption on runoff in the Krishna river basin (India), Hydrol. Earth Syst.
Sci., 10, 703–713, https://doi.org/10.5194/hess-10-703-2006, 2006.
Box, G. E. and Cox, D. R.: An analysis of transformations, J. Roy. Stat. Soc.
B, 26, 211–252, 1964.
Boyer, J. S.: Plant productivity and environment, Science, 218, 443–448,
1982.
Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W., and Vertessy, R.
A.: A review of paired catchment studies for determining changes in water
yield resulting from alterations in vegetation, J. Hydrol., 310,
28–61, 2005.
Burkhard, B., Kandziora, M., Hou, Y., and Müller, F.: Ecosystem service
potentials, flows and demands-concepts for spatial localisation, indication
and quantification, Landscape Online, 34, 1–32, 2014.
Chang, J., Wang, Y., Istanbulluoglu, E., Bai, T., Huang, Q., Yang, D., and
Huang, S.: Impact of climate change and human activities on runoff in the
Weihe River Basin, China, Quatern. Int., 380, 169–179, 2015.
Charlier, J.-B., Ladouche, B., and Maréchal, J.-C.: Identifying the
impact of climate and anthropic pressures on karst aquifers using wavelet
analysis, J. Hydrol., 523, 610–623, 2015.
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V.,
Aubinet, M., Buchmann, N., Bernhofer, C., and Carrara, A.: Europe-wide
reduction in primary productivity caused by the heat and drought in 2003,
Nature, 437, 529–533, 2005.
Dai, A.: Drought under global warming: a review, Wiley Interdisciplinary
Reviews, Climate Change, 2, 45–65, 2011.
Derbyshire, E., Meng, X., and Kemp, R. A.: Provenance, transport and
characteristics of modern aeolian dust in western Gansu Province, China, and
interpretation of the Quaternary loess record, J. Arid Environ.,
39, 497–516, 1998.
Duff, G. A., Myers, B. A., Williams, R. J., Eamus, D., O'Grady, A., and
Fordyce, I. R.: Seasonal Patterns in Soil Moisture, Vapour Pressure Deficit,
Tree Canopy Cover and Pre-dawn Water Potential in a Northern Australian
Savanna, Aust. J. Bot., 45, 211–224, 1997.
Ellison, D., Futter, M. N., and Bishop, K.: On the forest cover–water yield
debate: from demand- to supply-side thinking, Glob. Change Biol., 18,
806–820, 2012.
Farley, K. A., Jobbágy, E. G., and Jackson, R. B.: Effects of
afforestation on water yield: a global synthesis with implications for
policy, Glob. Change Biol., 11, 1565–1576, 2005.
Feng, X., Fu, B., Piao, S., Wang, S., Ciais, P., Zeng, Z., Lü, Y., Zeng,
Y., Li, Y., and Jiang, X.: Revegetation in China [rsquor] s Loess Plateau is
approaching sustainable water resource limits, Nat. Clim. Change, 6,
1019–1022, 2016a.
Feng, X., Wei, C., Fu, B., and Lü, Y.: The role of climatic and
anthropogenic stresses on long-term runoff reduction from the Loess Plateau,
China, Sci. Total Environ., 571, 688–698, https://doi.org/10.1016/j.scitotenv.2016.07.038, 2016b.
Fu, C., Jiang, Z., Guan, Z., He, J., and Xu, Z.: Climate Extremes and
Related Disasters in China, Springer Berlin Heidelberg, 2008.
Gan, Y., Siddique, K. H., Turner, N. C., Li, X.-G., Niu, J.-Y., Yang, C.,
Liu, L., and Chai, Q.: Ridge-furrow mulching systems—an innovative
technique for boosting crop productivity in semiarid rain-fed environments,
Adv. Agron., 118, 429–476, 2013.
Ghulam, A., Qin, Q., Teyip, T., and Li, Z. L.: Modified perpendicular
drought index (MPDI): a real-time drought monitoring method, ISPRS J. Photogramm., 62, 150–164, 2007.
Goddard, S., Harms, S. K., Reichenbach, S. E., Tadesse, T., and Waltman, W.
J.: Geospatial Decision Support for Drought Risk Management, Commun. ACM, 46, 35–37, 2001.
Guo, A., Chang, J., Liu, D., Wang, Y., Huang, Q., and Li, Y.: Variations in
the precipitation–runoff relationship of the Weihe River Basin, Hydrol.
Res., 48, 295–310, 2016.
Hao, Z. and Singh, V. P.: Drought characterization from a multivariate
perspective: A review, J. Hydrol., 527, 668–678, 2015.
Hayes, M., Svoboda, M., Wardlow, B., Anderson, M., and Kogan, F.: Drought
monitoring: Historical and current perspectives, Remote sensing of drought,
94, 1–19, 2012.
Herbst, P. H., Bredenkamp, D. B., and Barker, H. M. G.: A technique for the
evaluation of drought from rainfall data, J. Hydrol., 4, 264–272,
1966.
Hu, S., Zhi-Mao, G., and Jun-Ping, Y.: The impacts of urbanization on soil
erosion in the Loess Plateau region, J. Geogr. Sci., 11,
282–290, 2001.
Lü, Y., Zhang, L., Feng, X., Zeng, Y., Fu, B., Yao, X., Li, J., and Wu,
B.: Recent ecological transitions in China: greening, browning, and
influential factors, Sci. Rep.-UK, 5, 1–8, 2014.
Lee, T., Modarres, R., and Ouarda, T. B.: Data-based analysis of bivariate
copula tail dependence for drought duration and severity, Hydrol. Process., 27, 1454–1463, 2013.
Massey, F. J.: The Kolmogorov-Smirnov Test for Goodness of Fit, J. Am. Stat. Assoc., 46, 68–78, 1951.
McKee, T. B., Doesken, N. J., and Kleist, J.: The Relationship of Drought
Frequency and Duration to Time Scales, Proceeding of the 8th Conference on
Applied Climatology, 17, 179–183, 1993.
Michele, C., Salvadori, G., Vezzoli, R., and Pecora, S.: Multivariate
assessment of droughts: Frequency analysis and dynamic return period, Water Resour. Res., 49, 6985–6994, 2013.
Mirabbasi, R., Fakheri-Fard, A., and Dinpashoh, Y.: Bivariate drought
frequency analysis using the copula method, Theor. Appl. Climatol., 108, 191–206, 2012.
Mishra, A. K. and Singh, V. P.: A review of drought concepts, J. Hydrol., 391, 202–216, 2010.
Mohan, S. and Rangacharya, N. C. V.: A modified method for drought
identification, Hydrolog. Sci. J., 36, 11–21, 1991.
Moron, V.: Guinean and sahelian rainfall anomaly indices at annual and
monthly scales (1933–1990), Int. J. Climatol., 14,
325–341, 1994.
Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J., Glassy, J., Tian,
Y., Wang, Y., Song, X., Zhang, Y., and Smith, G.: Global products of
vegetation leaf area and fraction absorbed PAR from year one of MODIS data,
Remote Sens. Environ., 83, 214-231, 2002.
Naresh Kumar, M., Murthy, C. S., Sesha Sai, M. V. R., and Roy, P. S.: On the
use of Standardized Precipitation Index (SPI) for drought intensity
assessment, Meteorol. Appl., 16, 381–389, 2009.
Nourani, V., Khanghah, T., and Baghanam, A.: Application of Entropy Concept
for Input Selection of Wavelet-ANN Based Rainfall-Runoff Modeling, J.
Environ. Inform., 26, 52–70, 2015.
Palmer, W.: Meteorological drought, U.s.department of Commerce Weather Bureau
Research Paper, Department of Commerce Weather Bureau Research Paper 45,
58 pp., 1965.
Panagos, P., Borrelli, P., Meusburger, K., van der Zanden, E. H., Poesen,
J., and Alewell, C.: Modelling the effect of support practices (P-factor) on
the reduction of soil erosion by water at European scale, Environ. Sci. Policy, 51, 23–34, 2015.
Petrone, K. C., Hughes, J. D., Van Niel, T. G., and Silberstein, R. P.:
Streamflow decline in southwestern Australia, 1950–2008, Geophys. Res.
Lett., 37, L11401, https://doi.org/10.1029/2010GL043102, 2010.
Raziei, T., Saghafian, B., Paulo, A. A., Pereira, L. S., and Bordi, I.:
Spatial patterns and temporal variability of drought in Western Iran, Water Resour. Manag., 23, 439–455, 2009.
Saft, M., Western, A. W., Zhang, L., Peel, M. C., and Potter, N. J.: The
influence of multiyear drought on the annual rainfall-runoff relationship:
An Australian perspective, Water Resour. Res., 51, 2444–2463, 2015.
Savenije, H. H.: The runoff coefficient as the key to moisture recycling,
J. Hydrol., 176, 219–225, 1996.
Sheffield, J., Goteti, G., Wen, F., and Wood, E. F.: A simulated soil
moisture based drought analysis for the United States, J. Geophys.
Res.-Atmos., 109, D24108, https://doi.org/10.1029/2004JD005182, 2004.
Shi, C., Zhou, Y., Fan, X., and Shao, W.: A study on the annual runoff
change and its relationship with water and soil conservation practices and
climate change in the middle Yellow River basin, Catena, 100, 31–41, 2013.
Shiau, J. T.: Fitting Drought Duration and Severity with Two-Dimensional
Copulas, Water Resour. Manag., 20, 795–815, 2006.
Steinemann, A. C. and Cavalcanti, L. F.: Developing multiple indicators and
triggers for drought plans, J. Water Res. Plan. Man., 132, 164–174, 2006.
Sun, S., Barraud, S., Branger, F., Braud, I., and Castebrunet, H.: Urban
hydrologic trend analysis based on rainfall and runoff data analysis and
conceptual model calibration, Hydrol. Process., 31, 1349–1359, 2016.
Tian, H., Melillo, J. M., Kicklighter, D. W., Mcguire, A. D., Helfrich, J.
V. K., Moore, B., and Vörösmarty, C. J.: Effect of interannual
climate variability on carbon storage in Amazonian ecosystems, Nature, 396,
664–667, 1998.
Wang, S., Fu, B., Piao, S., Lü, Y., Ciais, P., Feng, X., and Wang, Y.:
Reduced sediment transport in the Yellow River due to anthropogenic changes,
Nat. Geosci., 9, 38–41, 2015.
Wang, X.-J., Cai, H.-J., Zhang, X., Wang, J., and Zhai, J.: Analysis of
changing characteristics and tendency of runoff and sediment transport in
Huangfuchuan River watershed, Res. Soil Water Conserv., 16, 222–226, 2009.
Wang, Z.-J., Jiao, J.-Y., Su, Y., and Chen, Y.: The efficiency of
large-scale afforestation with fish-scale pits for revegetation and soil
erosion control in the steppe zone on the hill-gully Loess Plateau, Catena,
115, 159–167, 2014.
Wilhite, D. A.: Drought as a natural hazard: Concepts and definitions,
Drought A Global Assessment, 1, 3–18, 2000.
Xia, Y., Ek, M. B., Peters-Lidard, C. D., Mocko, D., Svoboda, M., Sheffield,
J., and Wood, E. F.: Application of USDM statistics in NLDAS-2: Optimal
blended NLDAS drought index over the continental United States, J.
Geophys. Res.-Atmos., 119, 2947–2965, 2014.
Yan, H., Wang, S. Q., Wang, J. B., Lu, H. Q., Guo, A. H., Zhu, Z. C., Myneni,
R. B., and Shugart, H. H.: Assessing spatiotemporal variation of drought in
China and its impact on agriculture during 1982–2011 by using PDSI indices
and agriculture drought survey data, J. Geophys. Res.-Atmos., 121,
2283–2298, 2016.
Zhang, X., Zhang, L., Zhao, J., Rustomji, P., and Hairsine, P.: Responses of
streamflow to changes in climate and land use/cover in the Loess Plateau,
China, Water Resour. Res., 44, W00A07, https://doi.org/10.1029/2007WR006711, 2008.
Zheng, H., Li, Y., Robinson, B. E., Liu, G., Ma, D., Wang, F., Lu, F.,
Ouyang, Z., and Daily, G. C.: Using ecosystem service trade-offs to inform
water conservation policies and management practices, Front. Ecol.
Environ., 14, 527–532, 2016.
Zheng, H. X., Zhang, L., Zhu, R. R., Liu, C. M., Sato, Y., and Fukushima,
Y.: Responses of streamflow to climate and land surface change in the
headwaters of the Yellow River Basin, Water Resour. Res., 45, 641–648,
2009.
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais,
P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E.,
Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S.,
Peñuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy, N., Wang,
X., Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.: Greening of the
Earth and its drivers, Nature Climate Change, 6, 791–795, https://doi.org/10.1038/nclimate3004, 2016.
Short summary
We characterized drought by linking climate anomalies with the change in precipitation–runoff relationships in China's Loess Plateau, where drought is of major concern for revegetation. Multi-year drought causes a change in the precipitation–runoff relationship in this water limited area. The drought causing a decrease in runoff ratio is vital to ecosystem management. The revegetation in the Loess Plateau should live with the spatially varied drought.
We characterized drought by linking climate anomalies with the change in precipitation–runoff...
