Annual water balance model based on generalized proportionality relationship and its applications

The main goal of this dissertation research is to derive a type of conceptual models for annual water balance at the watershed scale. The proportionality relationship from the Soil Conservation Service Curve Number method was generalized to annual scale for deriving annual water balance model. As a result, a one-parameter Budyko equation was derived based on one-stage partitioning; and a four-parameter Budyko equation was derived based on two-stage partitioning. The derived equations balance model parsimony and representation of dominant hydrologic processes, and provide a new framework to disentangle the roles of climate variability, vegetation, soil and topography on long-term water balance. Three applications of the derived equations were demonstrated. Firstly, the four-parameter Budyko equation was applied to 165 watersheds in the United States to disentangle the roles of climate variability, vegetation, soil and topography on long-term water balance. Secondly, the one-parameter Budyko equation was applied to a large-scale irrigation region. The historical annual total water storage change were reconstructed for assessing groundwater depletion due to irrigation pumping by integrating the derived equation and the satellite-based GRACE (Gravity Recovery and Climate Experiment) data. Thirdly, the one-parameter Budyko equation was used to model the impact of willow treatment on annual evapotranspiration through a two-year field experiment in the Upper St. Johns River marshes. An empirical relationship between the parameter and willow fractional coverage was developed, providing a useful tool for predicting long-term response of evapotranspiration to willow treatment

Global assessment of the sensitivity of water storage to hydroclimatic variations

Observing basin water storage response due to hydroclimatic fluxes and human water use provides valuable insight to the sensitivity of water storage to climate change. Quantifying basin water storage changes due to climate and human water use is critical for water management yet remains a challenge globally. Observations from the Gravity Recovery and Climate Experiment (GRACE) mission are used to extract monthly available water (AW), representing the combined storage changes from groundwater and surface water stores. AW is combined with hydroclimatic fluxes, including precipitation (P) and evapotranspiration (ET) to quantify the hydroclimatic elasticity of AW for global basins. Our results detect consequential global water sensitivity to changes in hydroclimatic fluxes, where 25 % of land areas exhibit hydroclimatic elasticity of AW >10, implying that a 1 % change in monthly P-ET would result in a 10 % change in AW. Corroboration using a Budyko-derived metric substantiates our findings, demonstrating that basin water storage resilience to short-term water deficits is linked to basin partitioning predictability, and uniform seasonality of hydroclimatic fluxes. Our study demonstrates how small shifts in hydroclimate flux may affect available water storage potentially impacting billions globally

Assessing climate and terrestrial water storage controls on evapotranspiration variability: towards improved understanding of watersheds as coupled nature-human systems

Terrestrial evapotranspiration (ET) is an important eco-hydrologic process the couples the land surface water and energy budgets, links the water, carbon and nutrient cycle, and represents the largest water consumption from agricultural sector. Although advances have been made in monitoring and simulating terrestrial ET in last decades, there are still challenges in reconciling and cross-validating ET observation and numerical model simulation results. In particular, due to human interferences (such as agricultural irrigation), existing knowledge obtained under natural conditions is inapplicable to intensively managed watersheds. Therefore, there is a pressing need to develop hydrologic theory that depicts watersheds as coupled nature-human systems, and to apply knowledge derived from the complex system to validate and diagnose existing hydrologic observations and models, and explore the inter-connects of hydrologic dynamics across scales. This dissertation focuses on the ET temporal variability as a signature of watersheds as coupled nature-human systems, since ET variability is driven by the climatic fluctuations and modulated by hydrologic processes such as vegetation, snow dynamics and human water use. Based on general hydrologic laws on land surface water-energy coupling, this dissertation derives an Evapotranspiration Temporal VARiance Decomposition (ETVARD) framework for better understanding of both the climatic and hydrologic controls on ET temporal variability. Utilizing best available hydrologic observations, ETVARD quantifies the contributions from the variances and co-variances of climatic and terrestrial water storage change factors to ET variance at various temporal scale (e.g., monthly, seasonal and annual) for watersheds across a wide spectrum of climatic conditions (from humid to arid) under both natural and managed conditions. As such, we derive hydrologic knowledge from the congruence among theories, observations and models. For multi-variable and multi-source hydroclimatic observations, ETVARD provides an independent diagnosis tool to detect the possible biases and uncertainties in observations and land surface models. Using ETVARD as a benchmark for inter-comparison of observation and models and through five systematically designed experiments, this dissertation identifies the inconsistencies in ET variance estimates among theories, observations and models, assesses the quality of multiple ET products, and provides guidelines to improve land surface model structure in capturing ET variance for the contiguous United States. In particular, ETVARD identifies the temporal and spatial ET pattern changes due to extensive groundwater-based irrigation through a rea-world case study in the High Plains. The relation between ET and crop yield signatures (i.e., mean and variability) in rain-fed and irrigated crops reflects farmers’ irrigation behavior heterogeneity in the formation of ET patterns, depending on farmers’ preferences between profit-maximization and risk-aversion. In addition, a power-law statistical relationship between ET mean and variability is developed from independent ET observations. While the differences in climate conditions and vegetation structures are reflected by ecosystems’ water use preferences between consumption and variability, these water use preferences cluster on the same a power-law statistical relationship. The comprehensive assessment on ET variance in this dissertation provides a synthesis from existing theories, observations and simulations towards improved understanding of ET variance at the watershed system level. The knowledge discovered in the dissertation also provides guidelines for conjointly managing the mean and variability of watershed responses to both natural and human driving forces in the context of coupled nature-human systems

Hydrologic Observation, Model, and Theory Congruence on Evapotranspiration Variance: Diagnosis of Multiple Observations and Land Surface Models

This paper reconciles the state-of-the-art observations and simulations of evapotranspiration (ET) temporal variability through a diagnostic framework composed of an observation-model-theory triplet. Specifically, a confirmed theoretical tool, Evapotranspiration Temporal VARiance Decomposition (EVARD), is used as a benchmark to estimate ET monthly variance (σ2ET) across the contiguous United States (CONUS) with inputs including hydroclimatic observations, Gravity Recovery and Climate Experiment-based terrestrial water storage, four observation-based products (ETRSUW by the University of Washington, ETRSMOD16 from MOD16 Global Terrestrial ET Data Set, ETFLUXNET upscaled from of fluxtower observations, and ETGLEAM from Global Land Evaporation Amsterdam Model), and four operational land surface models (LSMs: MOSAIC, NOAH, NOAH-MP, and VIC). Five experiments are systematically designed to evaluate and diagnose possible errors and uncertainties in ET temporal variance estimated by the four observation-based ET products and the four LSM simulations. Based on the results of these experiments, the following diagnostic hypotheses regarding the uncertainty of the observation-based ET products are illustrated: ETRSUW captures the high σ2ET signals in the Midwest with negligible bias and moderate uncertainty over the contiguous United States; ETFLUXNET systematically underestimates σ2ET over CONUS but with the lowest level of uncertainty; ETRSMOD16 has medium bias with the highest level of uncertainty, and the spatial distribution of high σ2ET signal from ETRSMOD16 is different from other estimates; ETGLEAM has slight negative bias and medium uncertainty, and σ2ET in the West Coast is smaller than that from ETVARD. Regarding the LSMs, it is found that any of the four LSMs can be the best depending on a certain set of reference observations. The study reveals that LSMs have shown a reasonably worthy, though not perfect, capability in estimating ET and its variability in regions/aquifers with limited human interference. However, RS-based observations and theoretical estimates suggest that all the four LSMs examined in this study are not able to accurately predict the ET variability in regions/aquifers heavily influenced by human activities like Central Valley and High Plains aquifers; they all underestimate ET variability along the West Coast due to seasonal vegetation responses to Mediterranean climate and human water use. In addition, LSMs underestimate intraannual ET variance in California and the High Plains with underestimated terrestrial storage change components in ET variance, due to the inappropriate representation of groundwater pumping and its impact on ET and other hydrologic processes. This paper urges advancing hydrologic knowledge by finding congruence among models, data, and theories

Evaluating interannual water storage changes at watersheds in Illinois based on long-term soil moisture and groundwater level data

The annual water storage changes at 12 watersheds in Illinois are estimated based on the long-term soil moisture and groundwater level observations during 1981-2003. Storage change is usually ignored in mean annual and interannual water balance calculations. However, the interannual variability of storage change can be an important component in annual water balance during dry or wet years. Annual precipitation anomaly is partitioned into annual runoff anomaly, annual evaporation anomaly, and annual storage change. The estimated annual storage change ratios vary from -60% to 40% at the study watersheds. The interannual variability of evaporation is not strongly correlated with the interannual variability of precipitation, but is correlated with the interannual variations of effective precipitation. As a response to the interannual variability of precipitation, the interannual variation of evaporation is smaller than those of runoff and storage change. The effect of annual water storage change increases the correlation coefficients between annual evaporation ratio and climate dryness index. Therefore, interannual water storage changes need to be included in the estimation of evaporation and total water supply in the Budyko framework. Effective precipitation can be used as a substitute for precipitation when computing evaporation ratio and climate dryness index

Groundwater-dependent ecosystems: Recent insights from satellite and field-based studies

© 2015 Author(s). Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information; (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration; and (3) stable isotope analysis of water sources in the transpiration stream. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources. Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown.We provide a brief review of two case studies of the impacts of GW extraction and then provide an ecosystem-scale, multiple trait, integrated metric of the impact of differences in groundwater depth on the structure and function of eucalypt forests growing along a natural gradient in depth-to-groundwater. We conclude with a discussion of a depth-to-groundwater threshold in this mesic GDE. Beyond this threshold, significant changes occur in ecosystem structure and function

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage

Human-water interface in hydrological modeling: Current status and future directions

Over the last decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes at an unprecedented scale. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g., irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs are incorporating human impacts on hydrological cycle, yet human representations in hydrological models remain challenging. In this paper we provide a synthesis of progress in the development and application of human impact modeling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models

Climate and landscape controls on seasonal water balance at the watershed scale

The main goal of this dissertation is to develop a seasonal water balance model for evaporation, runoff and water storage change based on observations from a large number of watersheds, and further to obtain a comprehensive understanding on the dominant physical controls on intra-annual water balance. Meanwhile, the method for estimating evaporation and water storage based on recession analysis is improved by quantifying the seasonal pattern of the partial contributing area and contributing storage to base flow during low flow seasons. A new method for quantifying seasonality is developed in this research. The difference between precipitation and soil water storage change, defined as effective precipitation, is considered as the available water. As an analog to climate aridity index, the ratio between monthly potential evaporation and effective precipitation is defined as a monthly aridity index. Water-limited or energy-limited months are defined based on the threshold of 1. Water-limited or energy-limited seasons are defined by aggregating water-limited or energy-limited months, respectively. Seasonal evaporation is modeled by extending the Budyko hypothesis, which is originally for mean annual water balance; while seasonal surface runoff and base flow are modeled by generalizing the proportionality hypothesis originating from the SCS curve number model for surface runoff at the event scale. The developed seasonal evaporation and runoff models are evaluated based on watersheds across the United States. For the extended Budyko model, 250 out of 277 study watersheds have a Nash-Sutcliff efficiency (NSE) higher than 0.5, and for the seasonal runoff model, 179 out of 203 study watersheds have a NSE higher than 0.5. Furthermore, the connection between the seasonal parameters of the developed model and a variety of physical factors in the study watersheds is investigated. For the extended Budyko model, vegetation is identified as an important physical factor that related to the seasonal model parameters. However, the relationship is only strong in water-limited seasons, due to the seasonality of the vegetation coverage. In the seasonal runoff model, the key controlling factors for wetting capacity and initial wetting are soil hydraulic conductivity and maximum rainfall intensity respectively. As for initial evaporation, vegetation is identified as the strongest controlling factor. Besides long-term climate, this research identifies the key controlling factors on seasonal water balance: the effects of soil water storage, vegetation, soil hydraulic conductivity, and storminess. The developed model is applied to the Chipola River watershed and the Apalachicola River basin in Florida for assessing potential climate change impact on the seasonal water balance. The developed model performance is compared with a physically-based distributed hydrologic model of the Soil Water Assessment Tool, showing a good performance for seasonal runoff, evaporation and storage change