Water Resources Research

This study investigates a physical basis for heterogeneity in hydrological changes, which suggests a greater detectability in wet than dry regions. Wet regions are those where atmospheric demand is less than precipitation (energy limited), and dry regions are those where atmospheric demand is greater than precipitation (water limited). Long‐term streamflow trends in western North America and an analysis of Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models at global scales show geographically heterogeneous detectability of hydrological changes. We apply the Budyko framework and state‐of‐the‐art climate model data from CMIP5 to quantify the sensitivity and detectability of terrestrial hydrological changes. The Budyko framework quantifies the partitioning of precipitation into evapotranspiration and runoff components. We find that the terrestrial hydrological sensitivity is 3 times greater in regions where the hydrological cycle is energy limited rather than water limited. This additional source (the terrestrial part) contributes to 30–40% greater detectability in energy‐limited regions. We also quantified the contribution of changes in the catchment efficiency parameter that oppose the effects of increasing evaporative demand in global warming scenarios. Incorporating changes to the catchment efficiency parameter in the Budyko framework reduces dry biases in global runoff change projections by 88% in the 21st century.

Climate elasticity of runoff is an important indicator for evaluating the effects of climate change on runoff. Consequently, this paper proposes an analytical derivation of climate elasticity. Based on the mean annual water‐energy balance equation, two dimensionless numbers (the elasticities of runoff to precipitation and potential evaporation) were derived. Combining the first‐order differential of the Penman equation, the elasticities of runoff to precipitation, net radiation, air temperature, wind speed, and relative humidity were derived to separate the contributions of different climatic variables. The case study was carried out in the Futuo River catchment in the Hai River basin, as well as in 89 catchments of the Hai River and the Yellow River basins of China. Based on the mean annual of climatic variables, the climate elasticity in the Futuo River basin was estimated as follows: precipitation elasticity , net radiation elasticity , air temperature elasticity , wind speed elasticity , and relative humidity elasticity . In this catchment, precipitation decrease was mainly responsible for runoff decline, and wind speed decline had the second greatest effect on runoff. In the 89 catchments of the Hai River and the Yellow River basins of China, climate elasticity was estimated as follows: ranging from 1.6 to 3.9, ranging from −1.9 to −0.3, ranging from −0.11 to −0.02°C⁻¹, ranging from −0.8 to −0.1, and ranging from 0.2 to 1.9. Additional analysis shows that climate elasticity was sensitive to catchment characteristics.

Vegetation change is a critical factor that profoundly affects the terrestrial water cycle. Here we derive an analytical solution for the impact of vegetation changes on hydrological partitioning within the Budyko framework. This is achieved by deriving an analytical expression between leaf area index (LAI) change and the Budyko land surface parameter (n) change, through the combination of a steady state ecohydrological model with an analytical carbon cost‐benefit model for plant rooting depth. Using China where vegetation coverage has experienced dramatic changes over the past two decades as a study case, we quantify the impact of LAI changes on the hydrological partitioning during 1982–2010 and predict the future influence of these changes for the 21st century using climate model projections. Results show that LAI change exhibits an increasing importance on altering hydrological partitioning as climate becomes drier. In semiarid and arid China, increased LAI has led to substantial streamflow reductions over the past three decades (on average −8.5% in 1990s and −11.7% in 2000s compared to the 1980s baseline), and this decreasing trend in streamflow is projected to continue toward the end of this century due to predicted LAI increases. Our result calls for caution regarding the large‐scale revegetation activities currently being implemented in arid and semiarid China, which may result in serious future water scarcity issues here. The analytical model developed here is physically based and suitable for simultaneously assessing both vegetation changes and climate change induced changes to streamflow globally.

Temporal patterns of solute transport and transformation through the vadose zone are driven by the stochastic variability of water fluxes. This is determined by the hydrologic filtering of precipitation variability into infiltration, storage, drainage, and evapotranspiration. In this work we develop a framework for examining the role of the hydrologic filtering and, in particular, the effect of evapotranspiration in determining the travel time and delivery of sorbing, reacting solutes transported through the vadose zone by stochastic rainfall events. We describe a 1‐D vertical model in which solute pulses are tracked as point loads transported to depth by a series of discrete infiltration events. Numerical solutions of this model compare well to the Richards equation–based HYDRUS model for some typical cases. We then utilize existing theory of the stochastic dynamics of soil water to derive analytical and semianalytical expressions for the probability density functions (pdf's) of solute travel time and delivery. The moments of these pdf's directly relate the mean and variance of expected travel times to the water balance and show how evapotranspiration tends to reduce (and make more uncertain) the mass of a degrading solute delivered to the base of the vadose zone. The framework suggests a classification of different modes hydrologic filtering depending on hydroclimatic and landscape controls. Results suggest that variability in travel times decreases with soil depth in wet climates but increases with soil depth in dry climates. In dry climates, rare large storms can be an important mechanism for leaching to groundwater.

Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.

Effects of substantial increase in area of pine plantations from 1960 to 2000 on runoff in a large catchment in southeastern Australia are quantified. Reliable land use maps were prepared for 1960–1979, 1980–1989, and 1990–2000 conditions from various data sources. Land use changes in the subcatchments have occurred at varying rates (16 to 28%) with pines replacing pasture and native woody vegetation. On the basis of long‐term trends in rainfall‐runoff relationships, flow duration curves, and history of land use changes, it is shown that there is strong evidence of reduction in runoff over a wide range. Modeling methodology using a lumped catchment‐scale rainfall‐runoff model (SMAR) and landscape‐scale ecohydrological models (CLASS U3M‐1D, CLASS PGM, and 3PG+) was implemented in a catchment framework to partition the effects of land use change and climate variability during 1960–2000. Runoff reductions from land use change in the range 22–52 mm/yr are estimated for different subcatchments. Annual yield impact per 10% of the catchment forested (AYI/10%) from catchment‐scale modeling is estimated to vary between 14.3 to 19.2 mm/yr for the subcatchments. AYI/10% from landscape‐scale modeling is estimated to vary between 12.8 to 21.3 mm/yr.

This study extends the single parameter precipitation elasticity of streamflow index into a two parameter climate elasticity index, as a function of both precipitation and temperature, in order to assess climatic effects on annual streamflow. Application of the proposed index to two basins indicates that the single parameter precipitation elasticity index may give a general relationship between precipitation and streamflow in some cases, but that it cannot reflect the complicated non‐linear relationship among streamflow, precipitation and temperature. For example, for the Spokane River basin the climate elasticity of streamflow index varies from 2.4 to 0.2, for a precipitation increase of 20%, as temperature varies from 1°C lower to 1.8°C higher than the long term mean. Thus a 20% precipitation increase may result in a streamflow increase of 48% if the temperature is 1°C lower but only a 4% increase if the temperature is 1.8°C higher than the long‐term mean. The proposed method can be applied to other basins to assess potential climate change effects on annual streamflow. The results of the two case studies can inform planning of long‐term basin water management strategies taking into account global change scenarios.

Effect of climate change and catchment change on the long‐term water balance is of considerable interest at a range of spatial scales. The total differential of runoff within the Budyko framework, which has been widely used to attribute the change in runoff to the effect of climate and catchment changes, is not precise in which there is always some residual between the observed and estimated change in runoff. The objective of this study is to propose and evaluate a new partition method based on the Budyko complementary relationship for runoff. Algebraic identities have ensured that the change in runoff can be decomposed into two components precisely without any residuals using this complementary method. In addition, the complementary method allows estimation of the upper and lower bounds of the climate effect and catchment effect. The new method was compared with the total differential method and an extrapolation method for 15 catchments in Australia. Results show that the average range of the catchment effect using the complementary method was 6.7 mm for 14 of the 15 catchments, which is much smaller than that estimated with the total differential method (51.5 mm). The average of the upper and lower bounds was shown to be in good agreement with the effect of climate and catchment changes estimated using the extrapolation method (R² = 0.98 for both). Correlation analysis indicates that the average of these bounds is the best estimate of the magnitude of the climate and catchment effect for the 15 catchments examined.

Detailed characterization of dense nonaqueous phase liquid (DNAPL) source zone architecture (SZA) is essential for designing efficient remediation strategies. However, it is difficult to characterize a highly irregular and localized SZA, because traditional drilling investigations provide limited information. With limited data, the estimation accuracy of traditional geostatistical methods is strongly affected by the parameterization of the prior description of the SZA. To improve characterization performance, we parameterized the DNAPL saturation field using a physics‐based approach. We trained a convolutional variational autoencoder (CVAE) using data from multiphase modeling that captures the physics of DNAPL infiltration. The trained CVAE network was used in SZA inversion to obtain an improved prior DNAPL saturation field, instead of the typical stationary prior covariances. We then integrated the CVAE network into an iterative ensemble smoother (ES), to formulate a joint inversion framework. To overcome difficulties from limited/sparse data, we incorporated hydrogeological and geophysical datasets in the proposed inversion framework. To evaluate the performance of our method, we conducted numerical experiments in a hypothetical heterogeneous aquifer with an intricate SZA. The results show that the CVAE was an effective and efficient parameterization method which can capture the DNAPL infiltration patterns better than a Gaussian prior. The improved prior, combined with multisource datasets, can result in better resolution, and overall improved SZA characterization. In contrast to the standard ES method, the proposed framework reconstructed the SZA more accurately. We also demonstrated that DNAPL depletion behavior and dissolved concentration profiles can be predicted accurately using the estimated SZA.

Quản lý tài nguyên nước (WRM) nhằm phát triển bền vững gặp nhiều thách thức ở các khu vực có mạng lưới giám sát thực địa thưa thớt. Sự tăng trưởng theo cấp số nhân của thông tin dựa trên vệ tinh trong thập kỷ qua đã cung cấp cơ hội chưa từng thấy để hỗ trợ và cải thiện WRM. Hơn nữa, những rào cản truyền thống đối với việc tiếp cận và sử dụng dữ liệu vệ tinh đang dần giảm bớt khi những đổi mới công nghệ cung cấp cơ hội quản lý và phân phối nguồn thông tin phong phú này đến với nhiều đối tượng hơn. Chúng tôi xem xét nhu cầu dữ liệu cho WRM và vai trò mà cảm biến từ xa vệ tinh có thể đóng góp để lấp đầy khoảng trống và nâng cao WRM, tập trung vào khu vực Mỹ Latinh và Caribe làm ví dụ cho một khu vực có tiềm năng phát triển tài nguyên của mình hơn nữa và giảm thiểu tác động của các mối nguy thủy văn. Chúng tôi đánh giá công nghệ hiện tại cho các biến số liên quan, các nhiệm vụ vệ tinh hiện tại và sản phẩm, cách chúng đang được các cơ quan quốc gia trong khu vực Mỹ Latinh và Caribe sử dụng hiện nay, cũng như các thách thức trong việc cải thiện tính hữu dụng của chúng. Chúng tôi thảo luận về tiềm năng của các nhiệm vụ mới được ra mắt, sắp được triển khai và dự kiến có thể cải thiện và biến đổi việc đánh giá và giám sát tài nguyên nước. Những thách thức liên tục về độ chính xác, mẫu và tính liên tục vẫn cần được giải quyết, và những thách thức thêm về khối lượng dữ liệu khổng lồ mới cần vượt qua để tận dụng tốt nhất tiện ích của thông tin dựa trên vệ tinh trong việc cải thiện WRM.