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Summary Karst landform represents about 10% of the continental area and plays key roles in water supplies for almost a quarter of the global population. Knowledge of ecohydrological responses of karst landform to climate change is critical for both water resources management and ecological protection in these regions. This study investigated the effects of karst landform on the elasticity of actual evapotranspiration (derived by the Budyko equation), estimated the contribution of climate change and evaluated the implications, on the basis of 13 typical catchments that have different karst landform coverages in southwest China. Catchment properties, including the vegetation coverage, portion of karst landform (POK), drainage area, surface roughness, mean topographic wetness index, mean slope, and mean aspect, were selected to test the influencing factors for the elasticity of actual evapotranspiration. Results indicate that POK is the most influencing factor for the elasticity of actual evapotranspiration in this region. Moreover, the actual evapotranspiration in karst catchments is more sensitive to precipitation change and less sensitive to the potential evapotranspiration change than that in the non-karst catchments. On the other hand, the contribution of climate change to actual evapotranspiration was generally negative in this region. Furthermore, relatively large negative contributions mainly occurred in the karst-dominated catchments, suggesting that the karst catchments were exposed to higher degradation stress brought by the climate change than that in non-karst catchments. [ABSTRACT FROM AUTHOR]

• Introducing climate (CS) and vegetation seasonality (VS) into the Budyko framework. • CS and VS jointly contribute more than the changes in P and ET 0 in water partitioning. • In average the contributions of VS and CS in water partitioning are equally important. Climate and vegetation changes are main factors influencing water partitioning. However, their impacts on water partitioning are still not well understood. To revisit the interactions among climate, vegetation and water partitioning, this study introduces the climate seasonality (CS) and vegetation seasonality (VS) into the Budyko framework, by using a statistical approach combining the three-parameter Log-logistic probability distribution and multiple linear regression, based on the monthly 〈 P - ET 0 〉 (precipitation (P) minus potential evapotranspiration ( ET 0)) and Normalized Difference Vegetation Index (NDVI). This method is then validated and applied in 86 global catchments to quantify the contribution of climate and vegetation changes to evapotranspiration (ET). Results show that this model can predict well (mean R 2 = 0.81 ± 0.05, P < 0.05) the parameter n , a parameter reflecting the interactions between land surface and atmosphere in the Budyko framework. More importantly, CS and VS jointly control the variation in parameter n , and in average jointly contribute more (mean relative contribution of 57.1 ± 2.3 %) than the changes in P and ET 0 (mean of 42.9 ± 2.3%) to ET. These indicate that CS and VS are at least as important as the changes in P and ET 0 in affecting water balance. Furthermore, the VS contributes slightly lower (mean of 24.9 ± 0.3%) than the CS does (mean of 32.2 ± 2.3%), implying that CS and VS play comparable roles in water partitioning. These findings would be valuable for water resources management and assessing the impacts of climate and land surface changes on water balance in a gradually changing environment. [ABSTRACT FROM AUTHOR]

Karst landforms account for 10% of the Earths land surface, and it is well-known that water is a limiting factor for karst ecosystems because numerous underground fractures and conduits induce rapid drainage. Therefore, an understanding of ecosystem water consumptions (evapotranspiration) and environmental controls is particularly important for land management on karst landforms. This study compared the actual evapotranspiration ( AET) characteristics and analyzed the controls of three agroforestry ecosystems by field observations using a refitted ventilated-chamber, thermal dissipation probes and micro-lysimeters in a subtropical humid karst catchment from 12th March 2015 to 26th May 2016. Results show that: 1) the diurnal transpiration curves of trees plateau at noon with low fluctuations at a high level, while evapotranspiration curves of grass and crop ecosystems present single peaks; 2) AET of the forest-grass mixed ecosystem (7.64 ± 5.75 mm·day −1 ) was significantly higher than crop (4.24 ± 3.35 mm·day −1 ) and grass ecosystems (5.78 ± 3.53 mm·day −1 ); 3) AET of grass and crop ecosystems were most sensitive to temperature, while the forest-grass mixed ecosystem was more sensitive to leaf area index ( LAI ) than other factors; 4) AET of the forest-grass mixed ecosystem was more sensitive to deep soil moisture (>30 cm), while grass and crop ecosystems were more sensitive to shallow soil moisture (10 cm and 20 cm). This study suggests that soil water content was not key limit factors to AET in humid karst landscapes . However, LAI , which can be controlled by land management, heavily influenced AET rates and E / AET ( E , evaporation) ratio through changing water demand. [ABSTRACT FROM AUTHOR]

As one of the largest karst regions in the world, southwest China is experiencing severe soil erosion due to its special geological conditions, inappropriate land use, and lower soil loss tolerance. Knowledge and accurate estimations of changes in sediment discharge rates is important for finding potential measures to effectively control sediment delivery. This study investigated temporal variation in monthly sediment discharge ( SD ), and developed sediment rating curves and state-space model to estimate SD . Monthly water discharge, SD , precipitation, potential evapotranspiration, and normalized differential vegetation index during 2003–2015 collected from a typical karst catchment of Yujiang River were analyzed in present study. A Mann-Kendal test and Morlet wavelet analysis were employed to detect the changes in SD . Results indicated that a decreasing trend was observed in sediment discharge at monthly and annual scale. The water and sediment discharge both had a significant 1-year period, implying that water discharge has substantial influence on SD . The best state-space model using water discharge was a simple but effective model, accounting for 99% of the variation in SD . The sediment rating curves, however, represented only 78% of the variation in SD . This study provides an insight into the possibility of accurate estimation of SD only using water discharge with state-space model approach. State-space model is recommended as an effective approach for quantifying the temporal relationships between SD and its driving factors in karst regions of southwest China. [ABSTRACT FROM AUTHOR]

Southwest China represents one of the largest continuous karst regions in the world. It is estimated that around 1.7 million people are heavily dependent on water derived from karst springs in southwest China. However, there is a limited amount of water supply in this region. Moreover, there is not enough information on temporal patterns of spring discharge in the area. In this context, it is essential to accurately predict spring discharge, as well as understand karst hydrological processes in a thorough manner, so that water shortages in this area could be predicted and managed efficiently. The objectives of this study were to determine the primary factors that govern spring discharge patterns and to develop a state-space model to predict spring discharge. Spring discharge, precipitation (PT), relative humidity (RD), water temperature (WD), and electrical conductivity (EC) were the variables analyzed in the present work, and they were monitored at two different locations (referred to as karst springs A and B, respectively, in this paper) in a karst catchment area in southwest China from May to November 2015. Results showed that a state-space model using any combinations of variables outperformed a classical linear regression, a back-propagation artificial neural network model, and a least square support vector machine in modeling spring discharge time series for karst spring A. The best state-space model was obtained by using PT and RD, which accounted for 99.9% of the total variation in spring discharge. This model was then applied to an independent data set obtained from karst spring B, and it provided accurate spring discharge estimates. Therefore, state-space modeling was a useful tool for predicting spring discharge in karst regions in southwest China, and this modeling procedure may help researchers to obtain accurate results in other karst regions. [ABSTRACT FROM AUTHOR]

Southwest China, as one of the largest continuous karst areas in the world, is a severely eroded region due to its special geological condition. Thus, soil and water conservation measures such as dam construction have been extensively implemented in this region to control sediment delivery. However, it remains unclear how dam construction affects multiscale variability of sediment discharge (SD) and its potentially influential factors in southwest China. To assess this, annual SD, water discharge (WD), precipitation (PT), potential evapotranspiration (PET), and normalized differential vegetation index (NDVI) data from 1955 to 2015 were obtained from two karst watersheds of Liujiang (no large dams) and Hongshui (dam-controlled). These sites shared the similar climatic conditions. The Mann-Kendal test, Wilcoxon rank-sum test, and continuous wavelet transform analysis was used to detect the trends and periodicity in SD, and wavelet coherence analysis were employed to detect the temporal covariance between SD and WD, PT, PET, and NDVI. Results indicated that the multiscale variability of SD was strongly influenced by dam construction. The annual SD showed significant 4-year periodic oscillation in the Liujiang watershed, while no significant cycles were found in the Hongshui watershed. Dam construction exerted substantial influence on the multiscale correlations between SD and its associated factors. The time scales that the NDVI resonated with SD were concentrated on the periodicity of 2- and 3-year in the Liujiang watershed. In contrast, no significant periodicities were observed in the Hongshu watershed. This study yields a greater understanding of SD dynamics, and is helpful for better watershed management in karst areas of southwest China. [ABSTRACT FROM AUTHOR]

• GPP and ET were positively and linearly correlated to Rn and VPD in a karst forest. • WUE was negatively correlated to meteorological factors but positively to Bowen ratio. • WUE was not proportional to 1/VPD or 1/VPD0.5 but interactively responded to drivers. Water-use efficiency (WUE) is a key parameter that measures the balance between carbon gain and water loss in an ecosystem. Achieving better understanding of how WUE responds to environmental drivers is critical for revealing ecohydrological processes and mechanisms, and for biophysical modelling to investigate the interactions between vegetation and the changing environment. Karst landforms cover ∼10 % of the Earth's land surface; however, to date few studies have focused on the behaviours of WUE in karstic ecosystems. To fill these knowledge gaps, a two-year experiment was conducted to investigate the WUE and its drivers in a climax karst forest in southwestern China. Results showed that both the GPP (Gross Primary Production) and ET (evapotranspiration) showed exponential relationships to Ta (air temperature, P < 0.05), but linear relationships to Rn (net radiation, R 2 = 0.38 (GPP) and 0.78 (ET), P < 0.05) and VPD (water vapour pressure deficit, R 2 = 0.36 (GPP) and 0.28 (ET), P < 0.05), being quite different from those in other ecosystems. The reasons would be the different habits of the karstic plants, and the facts that the root zone water availability rarely dropped to low levels due to the frequent precipitation. The WUE, with the mean of 8.0 ± 4.8 mg CO 2 g−1 H 2 O, exhibited negative relationships to VPD (R 2 = 0.23, P < 0.05), Rn (R 2 = 0.28, P < 0.05), and Ta (air temperature, R 2 = 0.42, P < 0.05), and a positive linear relationship to the Bowen ratio (R 2 = 0.17, P < 0.05). Besides these, results also showed that the effects of a specific driver (e.g., VPD) on WUE was affected obviously by other factors (e.g., Ta, Rn), indicating that whether a driver is important or not to WUE, depends strongly on the environmental conditions. As the WUE-response formulas are often used to investigate and model the interactions between vegetation and environment, these findings suggested that the modelers should caution the versatility of the WUE-response formulas. [ABSTRACT FROM AUTHOR]

Quantifying the impacts of climate and human activities on water and sediment discharge has become a central topic in climate and hydrologic research. This issue, however, has so far received little attention in karst regions around the world. Seven karst catchments located in southwest China were chosen to explore water and sediment discharge responses to different driving factors during the period from the 1950s to 2011. The non-parametric Mann-Kendall test was used to detect both the trends and abrupt changes in water and sediment discharge. The double mass curve method was used to quantify the effects of climate and human activities on water and sediment discharge. Results indicated that the annual water discharge showed a decreasing trend in all catchments (−0.21 to −3.68 × 10 8 m 3 yr −1 ), and the sediment discharge exhibited a significant decreasing trend (−7 to −101 × 10 4 t yr −1 ) for six out of the seven catchments. A rapid decline (abrupt change) in sediment discharge occurred since 2000 for all except Liujiang catchment where the sediment discharge has a slight increase since 1983 as no large dams were constructed in this catchment. Specifically, the magnitude of reduction in sediment discharge (%) significantly increases with the extent of flow regulation as measured by the ratio of the area upstream the dam to the total catchment area for the seven catchments ( R 2 = 0.98, P < 0.01). This study demonstrated that water discharge was mainly influenced by precipitation, while sediment discharge was mainly influenced by human activities (relative contribution 70–111%, regardless of whether the effect is negative or positive). Ecological restoration played somehow important roles in the decrease in sediment discharge (negative relationships of sediment discharge with the Normalized Differential Vegetation Index (NDVI)), but dam construction was likely to be the principal cause of the significant decrease in sediment discharge. This study is of use for better catchment management in karst regions in southwest of China. [ABSTRACT FROM AUTHOR]