The Recharge Process and Influencing Meteorological Parameters Indicated by Cave Pool Hydrology in the Bare Karst Mountainous Area

Understanding the recharge and runoff processes of the vadose zone is significant for water resource management and utilization in karst mountain areas. Hydrological modeling of the vadose zone in karst caves has provided new methods of evaluating water resources in vadose zones. This paper provides modeling of vadose zone hydrology in a subtropical karst cave. The monitoring was conducted in Yuanyang Cave, Fengshan County, Guangxi Province, Southwest China. By monitoring the water level of a pool recharged by drop water in a cave, a model was established to calculate the natural leakage from the bottom and the infiltrated recharge from the vadose zone above. Combined with meteorological data records, the occurrence of recharge events in the vadose zone was analyzed. The correlation between them was established by multiple linear regression. The results showed that the infiltration ratio of precipitation was 20.88%. Recent rainfall of 4–7 days had shown a greater impact on recharge events than that of 3 days. The effect of evaporation was significant. The regression model in the cave pool was used to understand the hydrological process of the vadose zone, which provided a useful method for water resource management and evaluation in the remote karst mountain area.

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Runoff Predicting and Variation Analysis in Upper Ganjiang Basin under Projected Climate Changes

Sustainability ◽

10.3390/su11215885 ◽

2019 ◽

Vol 11 (21) ◽

pp. 5885 ◽

Cited By ~ 3

Author(s):

Chao Deng ◽

Weiguang Wang

Keyword(s):

Resource Management ◽

Water Resource ◽

Water Resource Management ◽

Hydrological Modeling ◽

Hydrologic Model ◽

Global Climate Models ◽

Balance Model ◽

Model Parameters ◽

The Mean ◽

Parameter Approach

Catchment runoff is significantly affected by climate condition changes. Predicting the runoff and analyzing its variations under future climates play a vital role in water security, water resource management, and the sustainable development of the catchment. In traditional hydrological modeling, fixed model parameters are usually used to transfer the global climate models (GCMs) to runoff, while the hydrologic model parameters may be time-varying. It is more appropriate to use the time-variant parameter for runoff modeling. This is achieved by incorporating the time-variant parameter approach into a two-parameter water balance model (TWBM) through the construction of time-variant parameter functions based on the identified catchment climate indicators. Using the Ganjiang Basin with an outlet of the Dongbei Hydrological Station as the study area, we developed time-variant parameter scenarios of the TWBM model and selected the best-performed parameter functions to predict future runoff and analyze its variations under the climate model projection of the BCC-CSM1.1(m). To synthetically assess the model performance improvements using the time-variant parameter approach, an index Δ was developed by combining the Nash–Sutcliffe efficiency, the volume error, the Box–Cox transformed root-mean-square error, and the Kling–Gupta efficiency with equivalent weight. The results show that the TWBM model with time-variant C (evapotranspiration parameter) and SC (water storage capacity of catchment), where growing and non-growing seasons are considered for C, outperformed the model with constant parameters with a Δ value of approximately 5% and 10% for the calibration and validation periods, respectively. The mean annual values of runoff predictions under the four representative concentration pathways (RCPs) exhibited a decreasing trend over the future three decades (2021–2050) when compared to the runoff simulations in the baseline period (1982–2011), where the values were about −9.9%, −19.5%, −16.6%, and −11.4% for the RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The decreasing trend of future precipitation exerts impacts on runoff decline. Generally, the mean monthly changes of runoff predictions showed a decreasing trend from January to August for almost all of the RCPs, while an increasing trend existed from September to November, along with fluctuations among different RCPs. This study can provide beneficial references to comprehensively understand the impacts of climate change on runoff prediction and thus improve the regional strategy for future water resource management.

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Water Resource Management: Moving from Single Risk-Based Management to Resilience to Multiple Stressors

Sustainability ◽

10.3390/su13158609 ◽

2021 ◽

Vol 13 (15) ◽

pp. 8609

Author(s):

Sarah Bunney ◽

Elizabeth Lawson ◽

Sarah Cotterill ◽

David Butler

Keyword(s):

Resource Management ◽

Water Resource ◽

Water Demand ◽

Water Resource Management ◽

Large Scale ◽

Multiple Stressors ◽

Meteorological Data ◽

Average Rainfall ◽

The Uk ◽

The Impact

Water resource management in the UK is multifaceted, with a complexity of issues arising from acute and chronic stressors. Below average rainfall in spring 2020 coincided with large-scale changes to domestic water consumption patterns, arising from the first UK-wide COVID-19 lockdown, resulting in increased pressure on nationwide resources. A sector wide survey, semi-structured interviews with sector executives, meteorological data, water resource management plans and market information were used to evaluate the impact of acute and chronic threats on water demand in the UK, and how resilience to both can be increased. The COVID-19 pandemic was a particularly acute threat: water demand increased across the country, it was unpredictable and hard to forecast, and compounding this, below average rainfall resulted in some areas having to tanker in water to ‘top up’ the network. This occurred in regions of the UK that are ‘water stressed’ as well as those that are not. We therefore propose a need to look beyond ‘design droughts’ and ‘dry weather average demand’ to characterise the management and resilience of future water resources. As a sector, we can learn from this acute threat and administer a more integrated approach, combining action on the social value of water, the implementation of water trading and the development of nationwide multi-sectoral resilience plans to better respond to short and long-term disruptors.

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Water resource management at catchment scales using lightweight UAVs: current capabilities and future perspectives

Journal of Unmanned Vehicle Systems ◽

10.1139/juvs-2015-0026 ◽

2016 ◽

Vol 4 (1) ◽

pp. 7-30 ◽

Cited By ~ 37

Author(s):

L. DeBell ◽

K. Anderson ◽

R.E. Brazier ◽

N. King ◽

L. Jones

Keyword(s):

Resource Management ◽

Water Resource ◽

Spatial Data ◽

Water Resource Management ◽

Temporal Distribution ◽

Cost Effective ◽

Hydrological Process ◽

Fine Scale ◽

Positional Accuracy ◽

The Right

Lightweight, portable unmanned aerial vehicles (UAVs) or ‘drones’ are set to become a key component of a water resource management (WRM) toolkit, but are currently not widely used in this context. In practical WRM there is a growing need for fine-scale responsive data, which cannot be delivered from satellites or aircraft in a cost-effective way. Such a capability is needed where water supplies are located in spatially heterogeneous dynamic catchments. In this review, we demonstrate the step change in hydrological process understanding that could be delivered if WRM employed UAVs. The paper discusses a range of pragmatic concepts in UAV science for cost-effective and practical WRM, from choosing the right sensor and platform combination through to practical deployment and data processing challenges. The paper highlights that multi-sensor approaches, such as combining thermal imaging with fine-scale structure-from-motion topographic models, are currently best placed to assist in WRM decision-making because they provide a means of monitoring the spatio-temporal distribution of sources, sinks, and flows of water through landscapes. The manuscript highlights areas where research is needed to support the integration of UAVs into practical WRM, for example, in improving positional accuracy through integration of differential global positioning system sensors, and developing intelligent control of UAV platforms to optimize the accuracy of spatial data capture.

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Evaluation of the Performance of Different Methods for Estimating Evaporation over a Highland Open Freshwater Lake in Mountainous Area

Water ◽

10.3390/w12123491 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3491

Author(s):

Xiaoni Meng ◽

Huizhi Liu ◽

Qun Du ◽

Lujun Xu ◽

Yang Liu

Keyword(s):

Climate Change ◽

Mass Transfer ◽

Resource Management ◽

Solar Radiation ◽

Water Resource ◽

Water Resource Management ◽

Freshwater Lake ◽

Mountainous Area ◽

Combination Methods ◽

Lake Evaporation

Lake evaporation is an important link connecting the water cycle and the surface energy cycle and remains one of the most uncertain terms in the local catchment’s water balance. Quantifying lake evaporation and its variability is crucial to improve water resource management and understand the response of the lake system towards climate change. In this study, we evaluated the performances of nine evaporation methods at different timescales and calibrated them by using the continuous eddy covariance (EC) observation data during 2015–2018 over Erhai Lake, a highland open freshwater lake situated in the Dali valley, China. The nine evaporation methods could be classified into combination methods (Bowen-ratio energy budget, Penman, Priestley–Taylor, DeBruin–Keijman and Brutsaert–Stricker), solar radiation-based methods (Jensen–Haise and Makkink) and Dalton-based method (mass transfer and Ryan–Harleman) based on their parameterization schemes. The Dalton-based Ryan–Harleman method is most suitable for estimating evaporation at daily to weekly scales, while the combination methods and solar radiation-based method had good estimates at monthly timescale. After calibration, the biases of the Jensen–Haise and Ryan–Harleman method were slightly reduced, while the biases of the Makkink and mass transfer methods were reduced substantially. The calibrated Jensen–Haise method with small annual bias (−2.2~2.8%) and simple input variables was applied to estimate the long-term trend of evaporation during 1981–2018. The annual total evaporation showed an insignificant increasing trend of 0.30 mm year−1, mainly caused by the significant rising air temperature. This study showed the performance of evaporation methods over water bodies had large discrepancies on different time scales, which indicated the importance of the choice of evaporation methods and provided instruction for water resource management of this region under climate change.

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