Terrestrial Water Balance Research Articles

Assessment of Three Common Methods for Estimating Terrestrial Water Storage Change with Three Reanalysis Datasets

AbstractTerrestrial water storage change (TWSC) plays a crucial role in the hydrological cycle and climate system. To date, methods including 1) the terrestrial water balance method (PER), 2) the combined atmospheric and terrestrial water balance method (AT), and 3) the summation method (SS) have been developed to estimate TWSC, but the accuracy of these methods has not been systematically compared. This paper compares the spatial and temporal differences of the TWSC estimates by the three methods comprehensively with the GRACE data during the 2002–13 period. To avoid the impact of different inputs in the comparison, three advanced reanalysis datasets are used, namely 1) the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) Reanalysis II (NCEP R2), 2) the ECMWF interim reanalysis (ERA-Interim), and 3) the Japanese 55-Year Reanalysis (JRA-55). The results show that all estimates with PER and AT considerably overestimate the long-term mean on a regional scale because the data assimilation in the reanalysis opens the water budget. The difficulty of atmospheric observation and simulation in arid and polar tundra regions is the documented reason for the failure of the AT method to represent the TWSC phase over 30% of the region found in this study. Although the SS result exhibited the best overall agreement with GRACE, the amplitude of TWSC based on SS differed substantially from that of GRACE and the similarity coefficient of the global distribution between the SS-derived estimate and GRACE is still not high. More detailed considerations of groundwater and human activities, for example, irrigation and reservoir impoundments, can help SS to achieve a higher accuracy.

Evaluation of A Regional Climate Model for the Eastern Nile Basin: Terrestrial and Atmospheric Water Balance

The study of water balance is considered here as a way to assess the performance of regional climate models and examine model uncertainty and as an approach to understanding regional hydrology, especially interactions between atmospheric and hydrological processes. We studied the atmospheric and terrestrial water balance over the Eastern Nile Basin (ENB) region using the weather research and forecasting (WRF) model. The model performance in simulating precipitation and surface air temperature is assessed by comparing the model output with the data from the Global Precipitation Climatology Center dataset for precipitation and from the University of Delaware for temperature. The results show that the simulated and observed values correlate well. In terms of water balance, the study region was found to be a sink for moisture, where the atmospheric convergence is negative during most of the time. Most of the precipitation originates from moisture fluxes from outside the domain, and the contribution of local evapotranspiration to precipitation is limited, with small values for the moisture recycling ratios year-round. The atmospheric moisture content does not show significant monthly or annual variation. The results indicate that the terrestrial water storage varies seasonally, with negative fluxes during most of the year, except June, July, and August, when most of the precipitation occurs.

Long‐term evapotranspiration rates for rainfed corn versus perennial bioenergy crops in a mesic landscape

AbstractPerennial cellulosic crops are promoted for their potential contributions to a sustainable energy future. However, a large‐scale perennial bioenergy production requires extensive land use changes through diversion of croplands or conversion of uncultivated lands, with potential implications for local and regional hydrology. To assess the impact of such land use conversions on ecosystem water use, we converted three 22 year‐old Conservation Reserve Program (CRP) grasslands and three 50+ year‐old conventionally tilled corn‐soybean crop fields (AGR) to either no‐till continuous maize (corn) or perennial (switchgrass or restored prairie) bioenergy crops. We also maintained one CRP grassland without conversion. We measured evapotranspiration (ET) rates on all fields for 9 years using eddy covariance methods. Results show that: (a) mean growing‐season ET rates for perennial crops were similar to the ET rate of the corn they replaced at the previously cultivated (AGR) field but ET rates for perennial crops at CRP fields were 5–9% higher than ET rate for corn on former CRP fields; and (b) mean nongrowing season ET rates for perennial fields were 11–15% lower than those for corn fields, regardless of land use history. On an annual basis, mean ET rates for perennial crops tended to be lower (4–7%) than ET rate of the corn that they replaced at AGR fields but ET rates for perennial crops and corn at CRP fields were similar. Over 9 years, mean ET rates for the same crop across land use histories were remarkably similar for corn, whereas for the perennial crops they were 4–10% higher at former CRP than at former AGR fields, mainly due to differences in growing season ET. Over the 9 years and across all fields, ET returned ~60% of the precipitation back to the atmosphere. These findings suggest that large‐scale substitution of perennial bioenergy crops for rainfed corn in mesic landscapes would have little if any (0 to −3%) impact on terrestrial water balances.

Evapotranspiration Estimation for Tibetan Plateau Headwaters Using Conjoint Terrestrial and Atmospheric Water Balances and Multisource Remote Sensing

AbstractSatellite remote sensing combined with water balance calculations provides a promising approach to estimating evapotranspiration (ET), a critical variable in water‐energy exchange. Here we compare ET estimates from terrestrial and atmospheric water balances, multisource remote sensing (AVHRR, GLEAM, and MOD16), and a land surface model (GLDAS NOAH) for headwaters on the Tibetan Plateau (TP), that is, headwaters of the Brahmaputra (HBR), Salween (HSR), Mekong (HMR), Yangtze (HYR), and Huang (Yellow; HHR) Rivers, for the 2003–2012 period. Results show that (1) ET estimated from terrestrial and atmospheric water balances agrees closely in three basins (HMR, HYR, and HHR) but has large discrepancies in the other two basins (HBR and HSR), mainly caused by uncertainties in the terrestrial water balance; (2) agreement between various ET products and water balance‐derived ET baselines is highest for GLEAM in two basins (HMR and HYR) and GLDAS NOAH in another two basins (HSR and HHR); and (3) large discrepancies between water balance‐derived ET and all ET products are found in the most glacierized HBR, which may reflect the importance of sublimation in the ET process. The decadal mean ET based on water balance‐derived ET baselines is highest in the HHR (447 mm/year) and HSR (430 mm/year) and lowest in the HBR (238 mm/year), ranging from 51% to 78% of mean precipitation in the five TP headwaters. These findings have important implications for ET estimation on the TP headwaters, which greatly influences downstream water availability.

Evaluation of Available Global Runoff Datasets Through a River Model in Support of Transboundary Water Management in South and Southeast Asia

Numerical models have become essential tools for simulating and forecasting hydro-meteorological variability, and to help better understand the Earth’s water cycle across temporal and spatial scales. Hydrologic outputs from these numerical models are widely available and represent valuable alternatives for supporting water management in regions where observations are scarce, including in transboundary river basins where data sharing is limited. Yet, the wide range of existing Land Surface Model (LSM) outputs makes the choice of dataset challenging in the absence of detailed analysis of the hydrological variability and quantification of associated physical processes. Here we focus on two of the world’s most populated transboundary river basins – the combined Ganges-Brahmaputra-Meghna (GBM) in South Asia and the Mekong in Southeast Asia – where downstream countries are particularly vulnerable to water related disasters in the absence of upstream hydro-meteorological information. In this study, several freely-available global LSM outputs are obtained from NASA’s Global Land Data Assimilation System (GLDAS) and from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-interim/Land (ERA-interim/Land) and used to compute river discharge across these transboundary basins using a river network routing model. Simulations are then compared to historical discharge to assess runoff data quality and identify best-performing models with implications for the terrestrial water balance. This analysis examines the effects of meteorological inputs, land surface models and their spatio-temporal resolution, as well as river network fineness and routing model parameters on hydrologic modeling performance. Our results indicate that the most recent runoff datasets yield the most accurate simulations in most cases, and suggest that meteorological inputs and the selection of the LSM are together the most influential factors affecting discharge simulations. Conversely, the spatial and temporal resolution of the LSM and river model have the least impact on the quality of simulated discharge, although the routing model parameters affect the timing of hydrographs.

Evaluation of the rescaled complementary principle in the estimation of evaporation on the Tibetan Plateau

Accurate quantification of the terrestrial water balance can improve our knowledge of regional water cycle changes, and deepen our understanding of evaporation in hydrological cycle and under climate change. However, sparse observation networks on the Tibetan Plateau (TP) prevent the reliable estimates of actual evaporation. Based on the China regional surface Meteorological Feature Dataset (CMFD) and the Global Land Surface Satellite (GLASS) product, we adopted the latest rescaled nonlinear complementary relationship (CR) to calculate the monthly actual evaporation (E) from 1982 to 2015. We analyzed the spatio-temporal variability of the annual E on the entire TP, and explored the main meteorological factors controlling the annual E and the regulation of multiyear average annual E in different vegetation zones from southeast to northwest. Our results indicated that the net radiation (Rn) and E exhibited a favorable agreement with monthly changes of the observed values; and E estimated by the CR explained 79–96% variation of the eddy covariance flux measurements. The multiyear average E was 373.12 mm yr−1 and displayed similar spatial patterns of decreasing from southeast to northwest with two remote sensing products (GLDAS_VIC, GLEAM_v3.3) and one hydrological model (Budyko). Additionally, based on the Mann-Kendall trend test, there were 21.56% of the TP with significant upward trend of annual E which mainly distributed in the area with dense glaciers. The Nyenchen Tanglha Mountains and Pamirs Plateau area had the most obvious upward trend, with up to over 6 mm yr−1. In a relative sense, the key meteorological elements which affected annual E on the TP were relative humidity (RH) (r = 0.63) and Rn (r = 0.56).

Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach

Abstract. Vegetation is known to have strong influence on evapotranspiration (ET), a major component of terrestrial water balance. Yet hydrological models often describe ET by methods unable to include the variability of vegetation characteristics in their predictions. To take advantage of the increasing availability of high-resolution open GIS data on land use, vegetation and soil characteristics in the boreal zone, a modular, spatially distributed model for predicting ET and other hydrological processes from grid cell to catchment level is presented and validated. An improved approach to upscale stomatal conductance to canopy scale using information on plant type (conifer/deciduous) and stand leaf-area index (LAI) is proposed by coupling a common leaf-scale stomatal conductance model with a simple canopy radiation transfer scheme. Further, a generic parametrization for vegetation-related hydrological processes for Nordic boreal forests is derived based on literature and data from a boreal FluxNet site. With the generic parametrization, the model was shown to reproduce daily ET measured using an eddy-covariance technique well at 10 conifer-dominated Nordic forests whose LAI ranged from 0.2 to 6.8 m2 m−2. Topography, soil and vegetation properties at 21 small boreal headwater catchments in Finland were derived from open GIS data at 16 m × 16 m grid size to upscale water balance from stand to catchment level. The predictions of annual ET and specific discharge were successful in all catchments, located from 60 to 68∘ N, and daily discharge was also reasonably well predicted by calibrating only one parameter against discharge measurements. The role of vegetation heterogeneity in soil moisture and partitioning of ET was demonstrated. The proposed framework can support, for example, forest trafficability forecasting and predicting impacts of climate change and forest management on stand and catchment water balance. With appropriate parametrization it can be generalized outside the boreal coniferous forests.

Assessment of terrestrial water balance using remote sensing data in South America

This study investigated the potential of assessing the water balance in South America, at multiple scales, using satellite remote sensing precipitation and evapotranspiration datasets, terrestrial water storage changes from Gravity Recovery and Climate Experiment (GRACE), and discharge measurements. The remote sensing precipitation datasets included those of the Tropical Rainfall Measuring Mission (TRMM) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP), whilst the ET constituents included the MODIS Global Evapotranspiration Project (MOD16) and the Global Land Evaporation Amsterdam Model (GLEAM). Uncertainties in precipitation and ET were evaluated using in situ measurements of 307 rain-gauge stations and 16 eddy covariance sites, respectively. The water balance closure and uncertainties were evaluated in 50 basins for the period 2003–2014, at different spatial scales and under different climatic conditions. Overall, MSWEP precipitation and GLEAM ET provided fewer uncertainties, whilst TRMM and MOD16 yielded greater bias and more errors. Better agreements between the TWSC from GRACE and the water balance were found in the large and medium-sized basins, with a root mean squared error (RMSE) of about 42%, whilst small basins and those located in regions with subtropical humid climates, where precipitation did not present strong seasonality, had a RMSE around 130%, indicating that climate conditions can influence the water balance closure. The TWSC from GRACE and the remote sensing water balance estimations were in agreement for more than half of the evaluated basins, mainly those located in tropical climate regions. Greater bias and more errors were found in the estimations of discharge in the semi-arid basins, with low runoff coefficients. Despite the water balance based on remote sensing estimations remaining a challenge due to the large uncertainties in precipitation, ET, and TWSC, our results showed their great potential for assessing terrestrial water-cycle dynamics and understanding their spatial and temporal variability at multiple scales.

Sensitivity of ASCE-Penman–Monteith reference evapotranspiration under different climate types in Brazil

Sensitivity analysis of reference evapotranspiration (ETo) plays a key role in the simplification and improvement of measurements of terrestrial water balance. The aim of this study was to perform sensitivity analyses of the ASCE-Penman–Monteith reference ET equation (EToPM) for different tropical and subtropical climates, where a quantitative understanding of water fluxes to the atmosphere is limited. Sensitivity coefficients were derived on a daily basis for maximum and minimum air temperature, solar radiation, vapor pressure deficit and wind speed at 2 m height using data from 44-year of actual measurements for calibration (1970–2014), for nine different climatic zones across Brazil. A multiple regression analysis was performed to estimate the relation between meteorological data and EToPM across climatic zones. Seasonal and annual average estimates were obtained by averaging daily values and spatial patterns of EToPM were obtained by interpolating meteorological data from all sampled locations. Five climate variables were used in the analysis, which revealed diverse effects on EToPM across seasons and climatic zones. In order of importance, EToPM was most sensitive to annual variation in vapor pressure deficit (VPD), wind speed (U2) and solar radiation (Rs) in all climate types. Our analysis also showed that VPD, calculated from measurements of relative humidity and temperature (T), are essential to accurately predict EToPM across tropical and subtropical climates. Due to the lack of direct meteorological measurements in many Brazilian regions, we recommend the adjustment of climate-driven hydrological fluxes predictions to the most sensitive variables, i.e., VPD, to improve the precision of reference ET losses. Our results will be useful in delineating the influence of different climatic variables in the ASCE Penman–Monteith model and in guiding new climatic modeling efforts in tropical and subtropical regions.

Variation in growing season water balance in central Victoria, Australia, in relation to large-scale climate drivers

The precipitation and evaporation records from 1972 to 2013 were analysed at five stations in central Victoria, Australia. The stations formed a north-south transect of sites across a distinct climatic gradient spanning the dry inland plains, the Great Dividing Range and the southern coastal zone. The focus was on the March–November ‘Growing Season’ when typically higher available moisture is critical for a variety of agricultural practices and water management across the region. Growing season rainfall trends were fairly consistent across all stations with ongoing declines generally observed in all months with the exception of November, with the most notable declines in April, May and October. Pan evaporation recorded display greater variation between stations with both significant positive and negative trends evident within the season across the station network. The influence of El Niño–Southern Oscillation and Indian Ocean Dipole on rainfall and pan evaporation was statistically significant, increasing through winter and peaking in spring at all stations. The Southern Annular Mode displayed marked intraseasonal influence which appeared to be highly location dependent. Interestingly, the tropical climate drivers displayed a stronger relationship with pan evaporation than rainfall over the analysis period. This highlighted the potential benefits of taking a broader terrestrial water balance (TWB) perspective of both pan evaporation and rainfall, a concept previously termed ‘Effective Rainfall’. Critically, this study shows the importance of understanding regional variation in TWB elements with respect to local topography and geographic location, as well as intraseasonal variations within the overall growing season.

Biophysical regulation of evapotranspiration in semiarid croplands

Water vapor exchange is a key component in terrestrial surface water balance. However, the biophysical regulation processes that control evapotranspiration (ET) in semiarid farmland areas have not been fully resolved. In this study, seasonal and interannual variances in ET and their environmental controls from 2009 to 2011 were investigated in a semiarid, rain-fed farmland using eddy covariance. One moderately dry year (2010) and two extremely dry years (2009 and 2011) were observed; however, 2009 (an extremely dry year) had the same weather condition as that of 2010 (a moderately dry year), and 2011 set out as different from the other two years. The results indicated that the maximum daily ET in the 2009 (4.4 mm d−1) and 2010 (4.7 mm d−1) growth seasons was higher than that in 2011 (3.0 mm d−1). Cumulative annual ET values were 310.6, 318.0, and 210.2 mm in 2009 to 2011, which were 109%, 96%, and 72% of the precipitation (PPT) received, respectively. The contribution of PPT in summer to the annual ET was more than that in autumn, and the extremely dry climate during the pregrowth stage and early spring period restricted the annual ET in 2011. The lowest annual ET in 2011 was caused by low daytime ET rather than nighttime ET. The strong power relationship (R2 = 0.85) between the decoupling coefficient (Ω) and the canopy conductance (gc) indicated that ET was sensitive to gc, and gc control on ET increased as the day progressed. The physiological controls of ET were associated closely with soil moisture, and drought had a strong effect on the ET response to environmental factors, such as incoming shortwave radiation and vapor pressure deficit. These results have important potential implications for understanding and modeling water cycle feedback to the increasing drought climate in the Loess Plateau characterized by serious soil and water loss.

High‐Resolution Modeling of Reservoir Release and Storage Dynamics at the Continental Scale

AbstractManmade reservoirs are important components of the terrestrial water balance. Thus, considering the hydro‐climatic effects of reservoirs is important in water cycle studies at a river basin to global scales; yet, reservoirs are represented poorly in large‐scale hydrological and climate models. Here we present a high‐resolution (5 km) continental‐scale reservoir storage dynamics and release scheme by enhancing existing schemes and adding critical novel parameterizations to improve reservoir storage and release simulations. The new scheme simulates river‐floodplain‐reservoir storages in an integrated manner considering their spatial and temporal variations. A new calibration scheme is also incorporated to better simulate reservoir dynamics considering cascade‐reservoir effects. Further, since no reservoir bathymetry data are available over large domains, we use a state‐of‐the‐art digital elevation model and reservoir extent data to derive reservoir bed elevation. The new scheme is integrated within the river‐floodplain routing scheme of a continental hydrological model LEAF‐Hydro‐Flood. Results from the simulation of ~1,900 reservoirs within the contiguous United States suggest that the model well captures the observed reservoir storage‐release dynamics. Comparison of our results with those from the existing schemes suggest a significant improvement; importantly, the new scheme reduces the excessive and frequent reservoir overfilling and underfilling. Comparison of results with satellite‐based surface water data shows that the model accurately reproduces the large‐scale patterns of reservoir‐floodplain inundation extents. It is expected that the results of this study will inform the incorporation of reservoirs in hyper‐resolution models to improve simulations of terrestrial water storage and flow and examine reservoir‐atmosphere interactions over large domains.

Partitioning evapotranspiration using an optimized satellite-based ET model across biomes

The partitioning of evapotranspiration (ET) is a critical factor in the terrestrial water balance and global water cycle, and understanding the partitioning across terrestrial biomes and the relationships between ET partitions and potential influencing factors is critical for predicting future ecosystem feedbacks. Based on an optimized Priestly-Taylor Jet Propulsion Laboratory model, we partitioned ET into three components transpiration (T), canopy interception evaporation (EI), and soil evaporation (ES). We found the components of EI to be significant with the ratio of EI to precipitation ranging from 0.02 to 0.29 across different biomes. The T/ET ratio ranged from 0.29 to 0.72 with obvious differences across biomes and with ratios generally lower than in previous studies with isotope-based methods. The (T + EI)/ET ratio was limited to a relatively narrow band from 0.57 to 0.86. The T/ET values show an obvious decreasing trend with increasing annual precipitation, but there was no significant correlation between T/ET and annual leaf area index.

Scenarios reveal pathways to sustain future ecosystem services in an agricultural landscape.

Sustaining food production, water quality, soil retention, flood, and climate regulation in agricultural landscapes is a pressing global challenge given accelerating environmental changes. Scenarios are stories about plausible futures, and scenarios can be integrated with biophysical simulation models to explore quantitatively how the future might unfold. However, few studies have incorporated a wide range of drivers (e.g., climate, land-use, management, population, human diet) in spatially explicit, process-based models to investigate spatial-temporal dynamics and relationships of a portfolio of ecosystem services. Here, we simulated nine ecosystem services (three provisioning and six regulating services) at 220×220 m from 2010 to 2070 under four contrasting scenarios in the 1,345-km2 Yahara Watershed (Wisconsin, USA) using Agro-IBIS, a dynamic model of terrestrial ecosystem processes, biogeochemistry, water, and energy balance. We asked (1) How does ecosystem service supply vary among alternative future scenarios? (2) Where on the landscape is the provision of ecosystem services most susceptible to future social-ecological changes? (3) Among alternative future scenarios, are relationships (i.e., trade-offs, synergies) among food production, water, and biogeochemical services consistent over time? Our results showed that food production varied substantially with future land-use choices and management, and its trade-offs with water quality and soil retention persisted under most scenarios. However, pathways to mitigate or even reverse such trade-offs through technological advances and sustainable agricultural practices were apparent. Consistent relationships among regulating services were identified across scenarios (e.g., trade-offs of freshwater supply vs. flood and climate regulation, and synergies among water quality, soil retention, and climate regulation), suggesting opportunities and challenges to sustaining these services. In particular, proactive land-use changes and management may buffer water quality against undesirable future climate changes, but changing climate may overwhelm management efforts to sustain freshwater supply and flood regulation. Spatially, changes in ecosystem services were heterogeneous across the landscape, underscoring the power of local actions and fine-scale management. Our research highlights the value of embracing spatial and temporal perspectives in managing ecosystem services and their complex interactions, and provides a system-level understanding for achieving sustainability of the food-water-climate nexus in agricultural landscapes.

Significant impacts of irrigation water sources and methods on modeling irrigation effects in the ACMELand Model

AbstractAn irrigation module considering irrigation water source and irrigation method has been incorporated into the ACME Land Model (ALM). Global numerical experiments were conducted to investigate irrigation effects and their sensitivity to irrigation water sources and irrigation methods. All simulations shared the same irrigation soil moisture target constrained by a global census data set of irrigation amounts. Irrigation has large impacts on terrestrial water balances especially in regions with extensive irrigation. Such effects depend on the irrigation water source: surface water‐fed irrigation decreases runoff and water table depth, while groundwater‐fed irrigation increases water table depth, and increases or decreases runoff depending on the pumping intensity. Irrigation effects also depend significantly on the irrigation method. Flood irrigation applies water in large volumes within short durations, resulting in much larger impacts on runoff and water table depth than drip and sprinkler irrigation. Differentiating the irrigation water source and method is important not only for representing the distinct pathways of how irrigation influences the terrestrial water balances, but also for estimating irrigation water use efficiency. Specifically, groundwater pumping has lower irrigation water use efficiency than irrigation relying on surface water withdrawal only due to enhanced recharge rates. Different irrigation methods also affect water use efficiency, with drip irrigation being the most efficient followed by sprinkler and flood irrigation. Our results highlight the importance of explicitly accounting for irrigation source and irrigation method, which are the least understood and constrained aspects in modeling irrigation water demand, water scarcity, and irrigation effects in Earth System Models.

Separating decadal global water cycle variability from sea level rise

Under a warming climate, amplification of the water cycle and changes in precipitation patterns over land are expected to occur, subsequently impacting the terrestrial water balance. On global scales, such changes in terrestrial water storage (TWS) will be reflected in the water contained in the ocean and can manifest as global sea level variations. Naturally occurring climate-driven TWS variability can temporarily obscure the long-term trend in sea level rise, in addition to modulating the impacts of sea level rise through natural periodic undulation in regional and global sea level. The internal variability of the global water cycle, therefore, confounds both the detection and attribution of sea level rise. Here, we use a suite of observations to quantify and map the contribution of TWS variability to sea level variability on decadal timescales. In particular, we find that decadal sea level variability centered in the Pacific Ocean is closely tied to low frequency variability of TWS in key areas across the globe. The unambiguous identification and clean separation of this component of variability is the missing step in uncovering the anthropogenic trend in sea level and understanding the potential for low-frequency modulation of future TWS impacts including flooding and drought.

The Transferability of Terrestrial Water Balance Components under Uncertainty and Nonstationarity: A Case Study of the Coastal Plain Watershed in the Southeastern USA

AbstractsThe challenges posed by nonstationarity in predicting catchment water balance components motivated this study to test the stationary versus nonstationarity hypothesis and detect changes in the watershed response to land use land cover (LULC) alterations, and climate variability and change. The focus is on a two‐step procedure that includes model calibration of Soil and Water Assessment Tool using a sequential Bayesian uncertainty algorithm (i.e. sequential uncertainty fitting), followed by nonstationary assessment of water balance component using extreme value analysis over an Atlantic coastal plain watershed in the southeastern USA. Analysis suggests that the uncertainty of Soil and Water Assessment Tool model is statistically aligned with LULC alterations that increased the sensitivity of Manning's roughness coefficient, transmission loss and the resistance of the soil matrix to water flow. Changes in LULC along with variability in the magnitude, timing and frequency of precipitation diminished surface runoff and groundwater contribution to the river system whereas it increased evapotranspiration with a substantial decline in water storage capacity. Nonstationary assessment of water balance using extreme value analysis model further revealed a functional form of stationary behaviour (no trends) prior to LULC alteration while large amplification was detected during post‐changes. The results and findings presented in this paper confirm our hypothesis about a combined effect of climate and LULC changes on hydrological functions and that variation of these fingerprints elucidates the presence of nonstationarity in the watershed system. Copyright © 2017 John Wiley & Sons, Ltd.

The Sensitivity of the Terrestrial Surface Energy and Water Balance Estimates in the WRF Model to Lower Surface Boundary Representations: A South Norway Case Study

Abstract A seasonal snow cover, expansive forests, a long coast line, and a mountainous terrain are features of Norway’s geography. Forests, ground snow, and sea surface temperature (SST) vary on time scales relevant for weather forecasting and climate projections. The mapping and model parameterization of these features vary in novelty, accuracy, and complexity. This paper investigates how increasing the influence of each of these features affects southern Norway’s surface energy and water balance in a regional climate model (WRF). High-resolution (3.7 km) experimental runs have been conducted over two consecutive hydrological years, including 1) heightening the boreal forest line (the Veg experiment), 2) increasing ground snow by altering the snow/rain criterion (the Snow experiment), or 3) increasing the SST (the SST experiment). The Veg experiment led to an increase in annual net radiation in the study area (by 3 W m−2), largely balanced out by an increase in latent heat flux. Moisture recycling increased, leaving only a negligible decrease in annual runoff. Surface temperature increased by 0.1°C, and its seasonal variability was dampened. Significant changes were also found outside the area of vegetation change. Snow decreased by 1.5 W m−2, despite slight increases in downward shortwave and longwave radiation. Both sensible heat flux and surface temperature decreased (by 1.3 W m−2 and 0.2°C, respectively), but the annual water balance remained mostly unchanged. The SST experiment led to increased downward and upward longwave radiation. Surface temperature was raised by 0.2°C. Advected oceanic moisture and thus both precipitation and runoff increased (by 2.5% and 2.8%, respectively).

Albedo climatology for European land surfaces retrieved from AVHRR data (1990–2014) and its spatial and temporal analysis from green‐up to vegetation senescence

AbstractSatellite‐based, long‐term records of surface albedo characterization that accurately capture spatial and temporal patterns are essential to develop climate models and to monitor the impact of land use changes on the terrestrial energy and water balance. This study presents the first Bidirectional Reflectance Distribution Function (BRDF) and albedo data set derived from the Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage reflectance data acquired on board National Oceanic and Atmospheric Administration and Meteorological Operational platforms from 1990 to 2014 over Europe. The objectives of this paper are to describe the data set's surface albedo climatology and anomalies in the visible, near‐infrared, and shortwave broadbands for the growing season months of May to September in order to facilitate utilization of the data by the climate modeling communities. The results demonstrate that the AVHRR BRDF and albedo data have temporal and spatial patterns that are appropriate for the underlying predominant land cover type and accurately reflect the associated climate variation. Visible and near‐infrared broadband albedo anomalies are found to be contrasting in most years, and their spatial distributions depict responses of vegetation to climate events (e.g., heat waves). Visible albedo of crops and near‐infrared albedo of pastures show a higher interannual variation than respective albedos of other snow‐free land covers, while the interannual standard deviations are found to be lower than 0.015. Our findings indicate the importance of taking into account the spectrally distinct variability of surface albedo when analyzing its complex spatiotemporal dynamics in climate‐related research.

Observation-based gridded runoff estimates for Europe (E-RUN version 1.1)

Abstract. River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct databases. Observed monthly runoff rates are subsequently tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950–December 2015) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring. The newly derived data are made publicly available at doi:10.1594/PANGAEA.861371.