An insight into the Palmer drought mechanism based indices: comprehensive comparison of their strengths and limitations

Considering the drawbacks of the original Palmer drought severity index (PDSI) in terms of its simplified hydrologic algorithm and spatio-temporal inconsistency, we compare six variants of PDSI derived from different combinations of two hydrologic algorithms and three standard processes so as to provide deep insights into the individual impacts of hydrological processing and standardization on final PDSI values as well as their combined effects. Investigations are conducted in whole Yellow River basin. On basis of 52 years’ (1961–2012) hydro-meteorological data, comprehensive analysis on multiple drought characteristics are carried out for each PDSI variant, combined with comparison of three crucial intermediate variables of PDSI. Results show that variable infiltration capacity (VIC) model based modification in the hydrologic accounting section significantly improve drought trends with more reasonable spatial distributions presented. For the statistical characteristics of drought areas and frequency, comparable performance is found between VIC-based modification and self-calibrating standard procedure-based modification, though they are derived from different mechanisms. However, in case of the coupling of these two modifications, indices derived from combined modifications perform poorly than single modification-based indices with unexpected high frequency of extreme events detected in certain regions. This reflects the complicated mechanism of PDSI and it is essential to propose an appropriate standardization to match the hydrological algorithm and further improve the performance of relevant drought index. With the crucial findings mentioned above, this study is promising to provide some theoretical supports and serve as a competent reference for future PDSI based researches.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatiotemporal analysis of climate variability (1971–2010) in spring and summer on the Loess Plateau,China

By using the Variable Infiltration Capacity model with Palmer Drought Severity Index (VIC‐PDSI) model and Standardized Precipitation Index (SPI), spatiotemporal trends of climate variation during the main growing seasons for plants of Loess Plateau between 1971 and 2010 were detected and characterized. The VIC‐PDSI model is established by combining the VIC model with PDSI. The simulation results and the grids system of VIC were applied to substitute for the two‐layer bucket‐type model to do the hydrological accounting, which could improve the physical mechanism of PDSI and expand its application range. Our results suggest that the climate of the study area has experienced a drying and warming trend during the past four decades. Apart from some individual years and regions, there was a perpetuation of water deficit over the Plateau both in spring and summer. The drought frequency increased from southeast to northwest in spring, while the drought frequency decreased from southeast to northwest in summer. The climate in the southern part of the Loess Plateau, accounting for 23.3% of the study region, showed a significant drying and warming trend in spring over the past four decades. The climate variability detected by VIC‐PDSI model shows good agreement with that monitored by SPI. Since a large part of the study region frequently suffered from water shortage during the main growing seasons for plants, people living in such drought‐prone areas should take measures to prevent the negative effects on agricultural production, reforestation, and regional food security caused by drought. Copyright © 2013 John Wiley & Sons, Ltd.     

Regional applicability of seven meteorological drought indices in China

The definition of a drought index is the foundation of drought research. However, because of the complexity of drought, there is no a unified drought index appropriate for different drought types and objects at the same time. Therefore, it is crucial to determine the regional applicability of various drought indices. Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment, and the observed soil moisture and streamflow in China, we evaluated the regional applicability of seven meteorological drought indices: the Palmer Drought Severity Index (PDSI), modified PDSI (PDSI_CN) based on observations in China, self-calibrating PDSI (scPDSI), Surface Wetness Index (SWI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing (CLM3.5/ObsFC). The results showed that the scPDSI is most appropriate for China. However, it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN; thus, the classification of dry and wet conditions should be adjusted accordingly. Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters. The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas. This is because contributions of temperature variation to drought are neglected in the SPI, but overestimated in the SPEI, when potential evapotranspiration is estimated by the Thornthwaite method in these areas. Consequently, the SPI and SPEI tend to induce wetter and drier results, respectively. The CLM3.5/ObsFC is suitable for China before 2000, but not for arid and semiarid areas after 2000. Consistent with other drought indices, the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations. Although the long-term trends of drought areas in China detected by these seven drought indices during 1961–2013 are consistent, obvious differences exist among the values of drought areas, which might be attributable to the definitions of the drought indices in addition to climatic change.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Improving drought predictability in Arkansas using the ensemble PDSI forecast technique

Drought prediction is important for improved water resources management and agriculture planning. Although Arkansas has suffered severe droughts and economic loss in recent years, no significant study has been done. This study proposes a local nonparametric autoregressive model with designed stochastic residual-resampling approach to produce ensemble drought forecasts with associated confidence. The proposed model utilizes historical climate records, including drought indices, temperature, and precipitation to improve the quality of the short-term forecast of drought indices. Monthly forecasts of Palmer Drought Severity Index (PDSI) in Arkansas climate divisions show remarkable skills with 2–3 month lead-time based on selected performance measure such as, Normalized Root Mean Square Error (NRMSE) and the Kuiper Skill Score (KSS). Rank histograms also show that the model captures the natural variability very well in the produced drought forecasts. The incorporation of categorical long-term precipitation prediction significantly enhances the performance of the monthly drought forecasts.     

Intercomparison of the total storage deficit index (TSDI) over two Canadian Prairie catchments

Retrieval of the terrestrial moisture storage dataset from the Gravity Recovery and Climate Experiment (GRACE) satellite remote sensing system is possible when the catchment of interest is of large spatial scale. These dataset are of paramount importance for the estimation of the total storage deficit index (TSDI), which enables the characterization of a particular drought event from the perspective of the terrestrial moisture storage over that catchment. Incidentally, the GRACE gravity signal over the 13,000 km² Upper Assiniboine River Basin on the drought-prone Canadian Prairie is so poor therefore making the computation of the total storage deficit index for this basin infeasible. Consequently, the estimation of the terrestrial moisture storage from other reliable sources becomes imperative in order to enable the computation of the TSDI over this basin.This study explores the utilization of the Variable Infiltration Capacity (VIC) model, a physically based, spatially distributed hydrologic model to simulate the total moisture storage over the Upper Assiniboine River Basin which was then employed in the estimation of the TSDI over this basin for subsequent characterization of the recent Prairie-wide drought. Interestingly, the temporal patterns in the computed TSDI from the VIC model reveal a strong resemblance with the same drought characterization undertaken over the larger adjacent Saskatchewan River Basin, which was accomplished utilizing terrestrial moisture storage from the GRACE-based approach. Additionally, these independent techniques employed in the characterization of the last Prairie drought over the two adjacently situated basins resulted in similar drought severity classification from the standpoint of the total moisture storage deficits over these basins. This study has therefore shown that in the computation of the total storage deficit index over small-scale catchments during anomalous climatic conditions that propagate extreme dryness through the terrestrial hydrologic systems, simulations of the total water storage from a structurally sound model such as the VIC model could be resourceful for the computation of the monthly total storage deficit index if no constraint is placed on the availability of accurate meteorological forcing.     

Identification of extreme events using drought indices and their impact on the Danube lower basin discharge

In this study extreme droughts and extremely wet periods in the Danube upper and middle basin (DUMB) have been highlighted with specific indices. The most widely used indices have been considered to estimate both the dry and wet phenomena severity and the frequency or spatio‐temporal extension. The climatic condition of 15 meteorological stations situated in the Danube basin has been evaluated using four indices: Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Weighted PDSI (WPLM) and Palmer Z‐index (ZIND). The four indices have been analysed separately for each of the four seasons between 1901 and 2000. First the internal structure of the time series of the four indices has been analysed separately. Then the overall temporal characteristic has been analysed by means of the principal component of the Multivariate Empirical Orthogonal Functions decomposition of the four indices (PC1‐MEOF). For the discharge in the Danube lower basin, station Orsova has been chosen, representing an integrator of the discharges from the DUMB. A very close connection has been found between Palmer indices and Danube discharge in all seasons (with correlation coefficients greater then 0.80) excepting the spring season. A classification in five classes of both the four indices separately and the PC1‐MEOF has been achieved in order to highlight extreme events. The impact of phenomena quantified by Palmer indices in DUMB upon discharges in Danube lower basin is evident. It was demonstrated in this study that the Greenland‐Balkan Oscillation (GBO) influences the south‐east European hydro‐climatic regime more than the North Atlantic Oscillation (NAO) Index. Copyright © 2016 John Wiley & Sons, Ltd.     

Retrieving Groundwater Depletion and Drought in the Tigris‐Euphrates Basin Between 2003 and 2015

Quantitative estimates of the groundwater depletion and droughts in the Tigris‐Euphrates Basin (TEB) can be useful for sustainably managing its water resources. Here, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to infer the monthly changes in the total water storage of the TEB from January 2003 to December 2015. Additionally, the data of altimetry and output from land surface models are used to remove the contributions from lake water changes and other hydrological factors to obtain the total groundwater depletion (TGWD), human‐driven groundwater depletion (HGWD), and climate‐driven groundwater depletion. We conclude that an alarming rate of decrease in the total water storage and the loss of TGWD have an “accelerating” trend, as the trend during 2007 to 2015 was 3.6 times that during 2003 to 2006. Moreover, the HGWD is 116.09 Gt, which accounts for 98% of the TGWD. Finally, the total storage deficit index (TSDI) is derived from the GRACE data to characterize the drought of the TEB. The results show that TSDI agrees well with the actual drought rather than the Palmer drought severity index (PDSI) and that the TEB has been undergoing a severe drought since September 2007 according to both the TSDI and PDSI. The research in this study provides an effective and unique method for understanding the hydrological processes and sustainable use of water resources in regions or countries with little data, which is essential for more efficient, sustainable, and cross‐boundary cooperative water resource management.     

A new method for establishing hydrologic fidelity of snow depth measurements based on snowmelt–runoff hydrographs

For snowmelt-driven flood studies, snow water equivalent (SWE) is frequently estimated using snow depth data. Accurate measurements of snow depth are important in providing data for continuous hydrologic simulations of such watersheds. A new hydrologic fidelity metric is proposed in this study to evaluate the potential contribution of particular snow depth datasets to flow characteristics using observed data and hydrologic modeling using the Variable Infiltration Capacity (VIC) model. Data-based hydrologic fidelity of snow depth measurements is defined as a categorical skill score between the snow depth in the watershed and the hydrograph peak or volume at the watershed outlet. Similarly, model-based hydrologic fidelity is defined as a categorical skill score between the model-simulated snow depth and the model-simulated hydrograph peak or volume. The proposed framework is illustrated using the Pecatonica River watershed in the USA, indicating which sites have a higher hydrologic fidelity, which is preferred in hydrologic studies.     

Scenarios of global municipal water-use demand projections over the 21st century

Abstract

A comparison study is presented of three methods for evaluating trends in drought frequency: the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and a new method for estimation of dry spells (DS), which is based on average daily temperature and precipitation, and takes into account the length of a spell. The methods were applied to climate data from 450 stations in the Elbe River basin for the period 1951–2003, as well as data from several stations with longer observed time series. Statistical methods were used to calculate trend lines and evaluate the significance of detected trends. The dry spells estimated with the new method show significant trends in the whole lowland part of the Elbe basin during the last 53 years, and at the 10% level almost everywhere in the German part of the basin excluding mountains and the area around the river mouth. The SPI and PDSI methods also revealed significant trends, but for smaller areas in the lowland. The new DS method provides a useful supplement to other drought indices for the detection of trends in drought frequency. Furthermore, the DS method was able to detect statistically significant trends in areas where the other two methods failed to find significant trends, e.g. in the loess region in the southwest of the German part of the basin, where small insignificant changes in climate can lead to significant changes in water fluxes. This is important, because the loess region is the area within the basin having the highest crop yields. Therefore, additional research has to be done to investigate possible impacts of detected trends on water resources availability, and possible future trends in drought frequency under climate change.     

Assimilating remotely sensed snow observations into a macroscale hydrology model

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas like the western United States. Current model-based forecasting approaches are limited by model biases and input data uncertainties. Remote sensing offers an opportunity for observation of snow properties, like areal extent and water equivalent, over larger areas. Data assimilation provides a framework for optimally merging information from remotely sensed observations and hydrologic model predictions. An ensemble Kalman filter (EnKF) was used to assimilate remotely sensed snow observations into the variable infiltration capacity (VIC) macroscale hydrologic model over the Snake River basin. The snow cover extent (SCE) product from the moderate resolution imaging spectroradiometer (MODIS) flown on the NASA Terra satellite was used to update VIC snow water equivalent (SWE), for a period of four consecutive winters (1999–2003). A simple snow depletion curve model was used for the necessary SWE–SCE inversion. The results showed that the EnKF is an effective and operationally feasible solution; the filter successfully updated model SCE predictions to better agree with the MODIS observations and ground surface measurements. Comparisons of the VIC SWE estimates following updating with surface SWE observations (from the NRCS SNOTEL network) indicated that the filter performance was a modest improvement over the open-loop (un-updated) simulations. This improvement was more evident for lower to middle elevations, and during snowmelt, while during accumulation the filter and open-loop estimates were very close on average. Subsequently, a preliminary assessment of the potential for assimilating the SWE product from the advanced microwave scanning radiometer (AMSR-E, flown on board the NASA Aqua satellite) was conducted. The results were not encouraging, and appeared to reflect large errors in the AMSR-E SWE product, which were also apparent in comparisons with SNOTEL data.     

亚洲和北美干湿变化及其与海表温度异常的关系

利用多通道奇异谱方法（MSSA）分析了1953~2003年亚洲和北美Palmer干旱指数（PDSI）与热带和北半球温带海洋海表面温度异常（SSTA）的主要周期振荡特征及其相互联系.结果表明：亚洲和北美PDSI以及SSTA均存在明显的3~6年的年际以及10年左右的年代尺度振荡;此外,亚洲PDSI还存在显著的6~8年的年际振荡.SSTA的年际振荡主要体现了ENSO的变化特征,而其年代尺度振荡的空间分布具有热带太平洋和北太平洋共同作用的类ENSO型.同时,MSSA的分析结果给出了亚洲和北美主要振荡信号的时间和空间演变特征.相关性分析表明,亚洲和北美PDSI的年际及年代尺度振荡均显示明显的对SSTA强迫信号的响应.对于年际振荡,亚洲PDSI对SSTA响应强于北美,但年代尺度振荡则反之.此外,亚洲和北美PDSI对于SSTA信号响应的关键区域也随时间尺度的不同而发生变化.亚洲的西西伯利亚、青藏高原东西两侧以及中西伯利亚东部在年际和年代尺度上均为受SSTA影响最显著的区域;在年际尺度上,北美中部地区的干湿变化与SSTA存在显著相关,而在年代尺度上,美国西部更易受SSTA年代尺度振荡的影响.     

Drought assessment using a multivariate drought index in the Luanhe River basin of Northern China

With climate change and the rapid increase in water demand, droughts, whose intensity, duration and frequency have shown an increasing trend in China over the past decades, are increasingly becoming a critical constraint to China’s sustainable socio-economic development, especially in Northern China, even more so. Therefore, it is essential to develop an appropriate drought assessment approach in China. To propose a suitable drought index for drought assessment, the Luanhe river basin in the northern China was selected as a case study site. Based on the Principal Component Analysis of precipitation, evapotranspiration, soil moisture and runoff, the three latter variables of which were obtained by using the Variable Infiltration Capacity land surface macro-scale hydrology model, a new multivariate drought index (MDI) was formulated, and its thresholds were determined by use of cumulative distribution function. To test the applicability of the newly developed index, the MDI, the standardized precipitation index (SPI) and the palmer drought severity index (PDSI) time series on a monthly scale were computed and compared during 1962–1963, 1968 and 1972 drought events. The results show that the MDI exhibited certain advantages over the PDSI and the SPI, i.e. better assessing drought severity and better reflecting drought evolution. The MDI formulated by this paper could provide a scientific basis for drought mitigation and management, and references for drought assessment elsewhere in China.     

Tropical drought patterns and their linkages to large-scale climate variability over Peninsular Malaysia

Ocean–atmosphere modes of climate variability in the Pacific and Indian oceans, as well as monsoons, regulate the regional wet and dry episodes in tropical regions. However, how those modes of climate variability, and their interactions, lead to spatial differences in drought patterns over tropical Asia at seasonal to interannual time scales remains unclear. This study aims to analyse the hydroclimate processes for both short- and long-term spatial drought patterns (3-, 6, 12- and 24-months) over Peninsular Malaysia using the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Palmer Drought Severity Index. Besides that, a generalized least squares regression is used to explore underlying circulation mechanisms of these spatio-temporal drought patterns. The tested drought indices indicate a tendency towards wetter conditions over Peninsular Malaysia. Based on principal component analysis, distinct spatio-temporal drought patterns are revealed, suggesting North–South and East–West gradients in drought distribution. The Pacific El Nino Southern Oscillation (ENSO), the South Western Indian Ocean (SWIO) variability, and the quasi-biennial oscillation (QBO) are significant contributors to the observed spatio-temporal variability in drought. Both the ENSO and the SWIO modulate the North–South gradient in drought conditions over Peninsular Malaysia, while the QBO contributes more to the East–West gradient. Through modulating regional moisture fluxes, the warm phases of the ENSO and the SWIO, and the western phases of the QBO weaken the southwest and northeast monsoon, leading to precipitation deficits and droughts over Peninsular Malaysia. The East–West or North–South gradients in droughts are related to the middle mountains blocking southwest and northeast moisture fluxes towards Peninsular Malaysia. In addition, the ENSO and QBO variations are significantly leading to short-term droughts (less than a year), while the SWIO is significantly associated with longer-duration droughts (2 years or more). Overall, this work demonstrates how spatio-temporal drought patterns in tropical regions are related to monsoons and moisture transports affected by the oscillations over the Pacific and Indian oceans, which is important for national water risk management.     

Trends in precipitation extremes over the Yellow River basin in North China: Changing properties and causes

The Mann–Kendall test, composite analysis, and 68 high‐quality meteorological stations were used to explore the spatiotemporal variations and causes of precipitation extremes over the Yellow River basin (YRB) during the period of 1960–2011. Results showed that (a) the YRB is characterized by decreases of most precipitation indices, excluding the simple daily intensity index, which has increasing trends in most locations, suggesting that the intensity of rainfall and the probability of occurrence of droughts have increased during the last decades. (b) Trends of extreme precipitation show mixed patterns in the lower reach of the YRB, where drought–flood disasters have increased. The increases in heavy rainfall and decreases in consecutive wet days in recent years over the northwestern portions of the YRB indicate that the intensity and frequency of above‐normal precipitation have been trending upward in domains. In the central‐south YRB, the maximum 1‐day precipitation (RX1day) and precipitation on extremely wet days (R99p) have significantly increased, whereas the number of consecutive dry days has declined; these trends suggest that the intensity of precipitation extremes has increased in those regions, although the frequency of extreme and total rainfall has decreased. (c) The spatial distributions of seasonal trends in RX1day and maximum 5‐day precipitation (RX5day) exhibited less spatial coherence, and winter is becoming the wettest season regionwide, particularly over the central‐south YRB. (d) There were multiple and overlapping cycles of variability for most precipitation indices, indicating variations of time and frequency. (e) Elevation is intimately correlated with precipitation indices, and a weakening East Asian summer monsoon during 1986–2011 compared to that in 1960–1985 may have played an important role in the declines in most indices over the YRB. Therefore, the combined effects from local and teleconnection forcing factors have collectively influenced the variations in precipitation extremes across the YRB. This study may provide valuable evidence for the effective management of water resources and the conduct of agricultural activities at the basin scale.     

QANAT SYSTEMS IN IRAN

Abstract

A fuzzy rule-based technique is used for modelling the relationship between climatic forcing and droughts in a Central/Eastern European country, Hungary. Two types of climatic forcing'called premises'are considered: atmospheric circulation patterns (CP) and El Niño Southern Oscillation (ENSO). Both the Hess-Brezowsky CP types and ENSO events influence the occurrence of droughts, but the ENSO signal is relatively weak in a statistical sense. The fuzzy rule-based approach is able to learn the high space—time variability of monthly Palmer Drought Severity Index (PDSI) and results in a proper reproduction of the empirical frequency distributions. The “engine” of the approach, the fuzzy rules, are ascertained from a subset called the learning set of the observed time series of premises (monthly CP frequencies and Southern Oscillation Index) and PDSI response. Then an independent subset, the validation set, is used to check how the application of fuzzy rules reproduces the observed PDSI.     

Influence of climate on alpine stream chemistry and water sources

The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 1994 to 2015, to explore how the partitioning of water sources and associated hydrologic resilience change in response to climate. Our results indicate that four water sources are significant contributors to Andrews Creek, including snow, rain, soil water, and talus groundwater. Seasonal patterns in source‐water contributions reflected the seasonal hydrologic cycle, which is driven by the accumulation and melting of seasonal snowpack. Flushing of soil water had a large effect on stream chemistry during spring snowmelt, despite making only a small contribution to streamflow volume. Snow had a large influence on stream chemistry as well, contributing large amounts of water with low concentrations of weathering products. Interannual patterns in end‐member contributions reflected responses to drought and wet periods. Moderate and significant correlations exist between annual end‐member contributions and regional‐scale climate indices (the Palmer Drought Severity Index, the Palmer Hydrologic Drought Index, and the Modified Palmer Drought Severity Index). From water year 1994 to 2015, the percent contribution from the talus‐groundwater end member to Andrews Creek increased an average of 0.5% per year (p < 0.0001), whereas the percent contributions from snow plus rain decreased by a similar amount (p = 0.001). Our results show how water and solute sources in alpine environments shift in response to climate variability and highlight the role of talus groundwater and soil water in providing hydrologic resilience to the system.     

Wetlandscape hydrologic dynamics driven by shallow groundwater and landscape topography

Wetlands play an important role in watershed eco-hydrology. The occurrence and distribution of wetlands in a landscape are affected by the surface topography and the hydro-climatic conditions. Here, we propose a minimalist probabilistic approach to describe the dynamic behaviour of wetlandscape attributes, including number of inundated wetlands and the statistical properties of wetland stage, surface area, perimeter, and storage volume. The method relies on two major assumptions: (a) wetland bottom hydrologic resistance is negligible; and (b) groundwater level is parallel to the mean terrain elevation. The approach links the number of inundated wetlands (depressions with water) to the distribution of wetland bottoms and divides, and the position of the shallow water table. We compared the wetlandscape attribute dynamics estimated from the probabilistic approach to those determined from a parsimonious hydrologic model for groundwater-dominated wetlands. We test the reliability of the assumptions of both models using data from six cypress dome wetlands in the Green Swamp Wildlife Management Area, Florida. The results of the hydrologic model for groundwater-dominated wetlands showed that the number of inundated wetlands has a unimodal dependence on the groundwater level, as predicted by the probabilistic approach. The proposed models provide a quantitative basis to understand the physical processes that drive the spatiotemporal hydrologic dynamics in wetlandscapes impacted by shallow groundwater fluctuations. Emergent patterns in wetlandscape hydrologic dynamics are of key importance not only for the conservation of water resources, but also for a wide range of eco-hydrological services provided by connectivity between wetlands and their surrounding uplands.