Variable Infiltration Capacity Hydrologic Model Research Articles

Slope Stability from a Hydrological Perspective: Taking Typical Soil Slope as an Example

In the traditional research of slope stability, it is difficult to continuously obtain the moisture content of soil in long time sequences. In combination with the precipitation, temperature, and vegetation cover data in the study area, the variable infiltration capacity hydrological model is used to estimate the daily variation of soil moisture content, which is used as a calculation condition for the analysis of slope stability. The results show that, from 1970 to 2010, the spatial‐temporal distribution of soil moisture content in the Weihe River Basin showed an increasing trend. Moreover, the shear strength of soil decreased, but the range was stable at approximately 2%. The strength reduction method based on the M‐C inscribed circle criterion (DP3) shows that the slope stability factor k had an increasing trend for over 40 y. The portion of the period with a k value higher than 1.2 is more than 85% of the entire period, that with a k value between 1 and 1.2 is approximately 9%, and that with a k value less than 1 is approximately 5.5%. The R/S analysis results show that the Hurst coefficients of the τ‐t curve and the k‐t curve are 0.5568 and 0.5888, respectively, and that the slope is in a state of no variation. Based on these factors, the present and future of the slope is in a stable state. This scheme is a method of studying slope stability based on hydrology, and it provides a modern alternative for soil shear strength calculation and geological hazard assessment.

Quantitative assessment of adaptive measures on optimal water resources allocation by using reliability, resilience, vulnerability indicators

Water resources allocation is facing great challenge, since hydrological series have shown non-stationarity with high uncertainty due to climate change and human activities. Adaptive measures are suggested to respond to the challenge. Aiming at quantitatively assess the impact of adaptive measures on optimal water resources allocation, we proposed a framework based on reliability, resilience and vulnerability indicators. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) of one global climate model were used to project future climate, and the variable infiltration capacity hydrological model was used to simulate streamflow. Three adaptive measures [water saving measure, water transfer project, dynamic control of flood limiting water levels (FLWLs) for reservoir operation] were combined to eight scenarios, then scenarios were applied to the allocation model to get different optimal allocation schemes which were assessed by RRV indicators. The results show that water saving measure decreases the vulnerability by 79 × 106 m3, water transfer project decreases the resilience by 17% in every scenario and dynamic control of FLWLs increases the reliability by 23.53% to the greatest scale. But the impacts of latter two adaptive measures are restricted to the areas which are geographically close to water supply projects. The uneven spatial distribution and decrease of streamflow will increase the risk of water shortage in the future. Optimal water allocation can reduce this risk and make 23 of 28 operational zones stable. Water saving measure is significantly valid in the rest 5 operational zones, but its impact is not positive to all water use sectors. Overall, our study helps understanding the interaction between adaptive measures and water resources system, and making guidelines for effective adaptation planning.

Understanding Reservoir Operating Rules in the Transboundary Nile River Basin Using Macroscale Hydrologic Modeling with Satellite Measurements

Abstract Challenges to manage and secure a sustainable water supply are expected to become more acute in Egypt as the lowermost riparian country of the Nile basin with the construction of new transboundary water infrastructures in Ethiopia and Sudan. To understand the impact of such transboundary water projects on Egypt, it is first necessary to develop a modeling tool that can simulate potential flow and reservoir scenarios inside Egypt without requiring in situ hydrologic or transboundary dam data that are typically unavailable. This study presents the water management value of a modeling framework to predict the current and future reservoir operating rules in the lower Nile basin using satellite Earth observations and hydrologic models. The platform comprises the Variable Infiltration Capacity (VIC) hydrologic model driven by high spatial and temporal resolution of satellite observations. Reservoir storage change is estimated using altimeter and visible imagery of lake area for Lake Nasser and then applied to infer reservoir operation for High Aswan Dam (HAD). The modeling framework based on satellite observations yielded a simulated streamflow at the outlet for Blue Nile basin (BNB) with a Nash–Sutcliffe efficiency of 0.68 with a correlation and RMSE of 0.94 and 1095 m3 s−1, respectively. Storage and outflow discharge of HAD were estimated for the period of 1998–2002 within 1.4% accuracy (0.076 km3 month−1) when compared with published reports. Because BNB controls the lion’s share of the variability to HAD inflow inside Egypt, the proposed modeling framework is appropriate for policy-makers to understand the implications of transboundary projects on the future water security of Egypt.

Accuracy evaluation of GPM multi-satellite precipitation products in the hydrological application over alpine and gorge regions with sparse rain gauge network

Abstract With the release of Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM products, hydrologists can obtain precipitation data with higher resolution and wider coverage. However, great uncertainties still exist in the accuracy and hydrological utility of these data in alpine and gorge regions with sparse gauge stations. In this study, the Lancang River Basin in China was used as an example, and near real-time products (IMERG-E and IMERG-L) and post-processed products (IMERG-F and TMPA 3B42-V7) were evaluated. Different indexes and methods were applied to evaluate the accuracy of these products. The variable infiltration capacity hydrological model was adopted to evaluate their hydrological utility. The following findings were obtained. (1) Compared with observed precipitation data, the near real-time products tend to underestimate, while the post-processed products tend to overestimate precipitation. The performance of the four products in winter is poor. (2) IMERG products offer improvements in two aspects: first, the near real-time products achieve good accuracy and second, the detectability and the accuracy in gorge areas have been greatly improved. (3) The near real-time products have the potential for hydrological applications. The best simulation result was obtained based on IMERG-F, followed by 3B42-V7, IMERG-E, and IMERG-L. (4) The four products can provide reliable precipitation data for the hydrological application over the Lancang River Basin.

Climatic Controls on Future Hydrologic Changes in a Subarctic River Basin in Canada

Abstract We describe a state-of-the-art framework for projecting hydrologic impacts due to enhanced warming and amplified moisture fluxes in the subarctic environment under anthropogenic climate change. We projected future hydrologic changes based on phase 5 of the Coupled Model Intercomparison Project global climate model simulations using the Variable Infiltration Capacity hydrologic model and a multivariate bias correction/downscaling method for the Liard basin in subarctic northwestern Canada. Subsequently, the variable importance of key climatic controls on a set of hydrologic indicators was analyzed using the random forests statistical model. Results indicate that enhanced warming and wetness by the end of century would lead to pronounced declines in annual and monthly snow water equivalent (SWE) and earlier maximum SWE. Prominent changes in the streamflow regime include increased annual mean and minimum flows, earlier maximum flows, and either increased or decreased maximum flows depending on interactions between temperature, precipitation, and snow. Using the variable importance analysis, we find that precipitation exerts the primary control on maximum SWE and annual mean and maximum flows, and temperature has the main influence on timings of maximum SWE and flow, and minimum flow. Given these climatic controls, the changes in the hydrologic indicators become progressively larger under the scenarios of 1.5°, 2.0°, and 3.0°C global mean temperature increases above the preindustrial period. Hence, the framework presented in this study provides a detailed diagnosis of the hydrologic changes as well as controls and interactions of the climatic variables, which could be generalized for understanding regional scale changes in subarctic/nival basins.

MOD-LSP, MODIS-based parameters for hydrologic modeling of North American land cover change

Earth systems models require gridded land surface properties to compute fluxes of water, energy, and carbon within the landscape and to the atmosphere. However, most parameter sets contain time-invariant properties despite their known variability. Here we present new MODerate Resolution Imaging Spectroradiometer (MODIS)-based land surface parameters (MOD-LSP) formatted for the Variable Infiltration Capacity (VIC) hydrologic model that account for seasonal and interannual variability and longer-term change over the continental United States, Mexico, and southern Canada at 0.0625° spatial resolution and monthly temporal resolution. MOD-LSP improves over previously-available parameter sets via: (1) land cover maps of higher native spatial resolution; (2) multiple versions corresponding to the land cover of years 1992, 2001, and 2011; (3) spatially-explicit mean annual cycles of land surface properties, including leaf area index, canopy fraction, and albedo, derived from 17 years of observations; and (4) additional 17-year time series of these properties. The MOD-LSP parameters are useful as inputs to the VIC model, as an example land surface scheme, to assess the hydrologic impacts of land cover change from interannual to decadal scales; and as stand-alone datasets characterizing the temporal variability of these properties as a function of land cover class.

Maximizing energy production from hydropower dams using short-term weather forecasts

This study explores the maximization of hydropower generation by optimizing reservoir operations based on short-term inflow forecasts derived from publicly available numerical weather prediction (NWP) models. Forecast fields from the NWP model of Global Forecast System (GFS) were used to force the Variable Infiltration Capacity (VIC) hydrologic model to forecast reservoir inflow for 1–16 days lead time. The optimization of reservoir operations was performed based on the forecast of inflow. The concept was demonstrated for two dams in the United States. Results showed that a significantly greater amount additional hydroelectric energy benefit can be derived consistently than the traditional operations without optimization and weather forecasts. Goals of flood control and dam safety were also not compromised when exploring opportunities for hydropower maximization. An alternate data-based technique was also demonstrated to improve the forecasting skill and efficiency. The study clearly underscores the additional value of weather forecasts that are available publicly and globally from NWP models for any dam location for hydropower maximization. Given the on-going effort to coordinate strategies for sustainable energy production from renewable energy sources, it is timely that this concept be expanded further to current hydropower dam sites around the world.

Projected Changes in the Frequency of Peak Flows along the Athabasca River: Sensitivity of Results to Statistical Methods of Analysis

Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be a temperature-induced shift in precipitation from snowfall towards rain along with changes in precipitation intensity and snowmelt timing, resulting in alterations in the frequency and magnitude of peak flow events. This study examines the potential future changes in the frequency and severity of peak flow events in the Athabasca River watershed in Alberta, Canada. The analysis is based on simulated flow data by the variable infiltration capacity (VIC) hydrologic model driven by statistically downscaled climate change scenarios from the latest coupled model inter-comparison project (CMIP5). The hydrological model projections show an overall increase in mean annual streamflow in the watershed and a corresponding shift in the freshet timing to an earlier period. The river flow is projected to experience increases during the winter and spring seasons and decreases during the summer and early fall seasons, with an overall projected increase in peak flow, especially for low frequency events. Both stationary and non-stationary methods of peak flow analysis, performed at multiple points along the Athabasca River, show that projected changes in the 100-year peak flow event for the high emissions scenario by the 2080s range between 4% and 33% depending on the driving climate models and the statistical method of analysis. A closer examination of the results also reveals that the sensitivity of projected changes in peak flows to the statistical method of frequency analysis is relatively small compared to that resulting from inter-climate model variability.

The Assimilation of Remote Sensing-Derived Soil Moisture Data into a Hydrological Model for the Mahanadi Basin, India

Accurate knowledge of the spatio-temporal variation in soil moisture provides insight into larger-scale hydrological processes and can, therefore, help in improving hydrological predictions. The strength of remote sensing for mapping surface soil moisture is well proven. In addition, data assimilation offers the opportunity to combine the advantages of modelling with those of remote sensing data to achieve higher accuracy and continuous improvement in hydrological forecasts. In this study, Advanced Microwave Scanning Radiometer for Earth observation science soil moisture product was assimilated into Variable Infiltration Capacity (VIC) hydrological model using Kalman filter data assimilation technique. Further, the updated multilayer spatio-temporal soil moisture distributions across the Mahanadi Basin, India, were simulated using the hydrological model. The VIC model was set up and parameterized using field-observed and remote sensing-derived data. Based on the sensitivity analysis of the model, the ‘four-parameter’ (Tmax, Tmin, Prec, and WS) meteorological forcing scenario was selected as the operational scenario. The output fluxes obtained from VIC were routed to simulate discharge at five stations for the calibration and validation of the model. With R2 and model efficiency values close to 0.95 and 0.99, respectively, the model was proven to be suitable for simulating the hydrological responses of the basin. Soil moisture was assimilated in the top soil layer of the model using the Kalman filter approach, and the multilayer soil moisture regime was generated using the modelling approach. The validation of soil moisture (assimilated) products proves that these products are better than remote sensing and traditionally modelled soil moisture products, in both spatial and temporal domains in terms of availability and accuracy.

Model-data fusion of hydrologic simulations and GRACE terrestrial water storage observations to estimate changes in water table depth

Despite numerous advances in continental-scale hydrologic modeling and improvements in global Land Surface Models, an accurate representation of regional water table depth (WTD) remains a challenge. Data assimilation of observations from the Gravity Recovery and Climate Experiment (GRACE) mission leads to improvements in the accuracy of hydrologic models, ultimately resulting in more reliable estimates of lumped water storage. However, the usually shallow groundwater compartment of many models presents a problem with GRACE assimilation techniques, as these satellite observations also represent changes in deeper soils and aquifers. To improve the accuracy of modeled groundwater estimates and allow the representation of WTD at finer spatial scales, we implemented a simple, yet novel approach to integrate GRACE data, by augmenting the Variable Infiltration Capacity (VIC) hydrologic model. First, the subsurface model structural representation was modified by incorporating an additional (fourth) soil layer of varying depth (up to 1000 m) in VIC as the bottom ‘groundwater’ layer. This addition allows the model to reproduce water storage variability not only in shallow soils but also in deeper groundwater, in order to allow integration of the full GRACE-observed variability. Second, a Direct Insertion scheme was developed that integrates the high temporal (daily) and spatial (∼6.94 km) resolution model outputs to match the GRACE resolution, performs the integration, and then disaggregates the updated model state after the assimilation step. Simulations were performed with and without Direct Insertion over the three largest river basins in California and including the Central Valley, in order to test the augmented model's ability to capture seasonal and inter-annual trends in the water table. This is the first-ever fusion of GRACE total water storage change observations with hydrologic simulations aiming at the determination of water table depth dynamics, at spatial scales potentially useful for local water management.

Relative impact of recent climate and land cover changes in the Godavari river basin, India

The Godavari river basin (GRB), the second largest river basin (312,800 \(\hbox {km}^{2}\)) in India, was considered in this study to quantify the relative hydrological impact of recent land cover (LC) changes and rainfall trends using the variable infiltration capacity hydrologic model. Three scenarios, namely, (i) LC change, (ii) climate change and (iii) LC and climate changes, were considered to isolate the hydrological implications of the LC changes from those of climate change. Results revealed that evapotranspiration is predominantly governed by LC change and that small changes in rainfall cause greater changes in the runoff. Although the spatial extent of LC change is higher, the climate change is the dominant driver of hydrological changes within the GRB. Thus, climate projections are the key inputs to study the impact on the river basin hydrology. The results provide insights into the impacts of the climate and LC changes on the basin. The methodology and results of the present study can be further considered for water resource planning within the river basin in view of the changing environment.

Improvements of the spatially distributed hydrological modelling using the HBV model at 1 km resolution for Norway

A robust hydrological modeling at a fine spatial resolution is a vital tool for Norway to simulate river discharges and hydrological components for climate adaptation strategies. However, it requires improvements of modelling methods, detailed observational data as input and expensive computational resources. This work aims to set up a distributed version of the HBV model with a physically based evapotranspiration scheme at 1 km resolution for mainland Norway and to calibrate/validate the model for 124 catchments using regionalized parameterizations. The Penman-Monteith equation was implemented in the HBV model and vegetation characteristics were derived from the Norwegian forest inventory combined with multi-source remote sensing data at 16 m spatial resolution. The estimated potential evapotranspiration (Ep) was compared with pan measurements and estimates from the MODerate Resolution Imaging Spectrometer (MOD16) products, the Global Land Evaporation Amsterdam Model (GLEAM) and Variable Infiltration Capacity (VIC) hydrological model. There are 5 climatic zones in Norway classified based on 4 temperature and precipitation indices. For each zone, the model was calibrated separately by optimizing a multi-objective function including the Nash-Sutcliff efficiency (NSE) and biases of selected catchments. In total, there are 85 catchments for calibration and 39 for validation. The Ep estimates showed good agreement with the measurements, GLEAM and VIC outputs. However, the MOD16 product significantly overestimates Ep compared to the other products. The discharge was well reproduced with the median daily NSE of 0.68/0.67, bias of −3%/−1%, Kling-Gupta efficiency (KGE) of 0.70/0.69 and monthly NSE of 0.80/0.78 in the calibration/validation periods. Our results showed a significant improvement compared to the previous HBV application for all catchments, with an increase of 0.08–0.16 in the median values of the daily NSE, KGE and monthly NSE. Both the temporal and spatial transferability of model parameterizations were also enhanced compared to the previous application.

A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China

AbstractClimate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.

A Coupled Glacier‐Hydrology Model and Its Application in Eastern Pamir

AbstractAn energy‐balance glacier‐melt scheme was coupled with the Variable Infiltration Capacity hydrology model (VIC‐glacier). The coupled model was setup at 30 m × 30 m grids and applied in the Muji basin in eastern Pamir. The model was validated with field measurements of albedo, glacier mass balance, and river runoff. The VIC‐glacier model showed a good correspondence with the observations in incoming shortwave radiation and albedo, with R2 of 0.70 and 0.32, respectively, during August–October 2012. Simulated glacier mass balance exhibited overall good agreements with the observations in ablation seasons, with R2 of 0.89 and root‐mean‐square error of 162.12 mm w.e. during 2011–2015. The model also reproduced discharge records, with R2 of 0.70–0.84, Nash‐Sutcliffe efficiency of 0.56–0.81, root‐mean‐square error of 0.29–0.45 m3/s, and negative relative error of 13.73–18.76% in melt seasons of 2014–2015. The glaciers in Muji basin had a low mean net radiation of 40 W/m2, large negative latent heat fluxes of −32 W/m2, and low melt energy of −21 W/m2 in ablation seasons, resembling the energy partitioning generally found in continental climates. About 60% of the positive energy supply was consumed by latent heat fluxes on the glaciers in Muji basin, while only about 40% of the positive energy supply was used for melting. Glaciers in the Muji basin experienced a mass balance of −812.18 mm over 2011–2015, corresponding to a water release of 4.42 × 106 m3.The VIC‐glacier model has a good potential of broader utility for the large basins with limited meteorological observations.

Assessment of the impact of climate change on hydropower potential in the Nanliujiang River basin of China

This study presents a model-based approach for assessing the impact of climate change on hydropower potential in the Nanliujiang River Basin of China. The variable infiltration capacity (VIC) hydrological model was proved to be able to do a good runoff simulation after 1000 times of calibration and validation, while it has greater uncertainty in the simulation of high flow and low flow. Coupling the VIC model with five climate models, the spatial and temporal distributions of water resources in the future are analyzed, and the uncertainty analysis shows that the multi-model ensemble results can more reliably reflect future climate change. Then, the hydropower potential of the whole river basin in the future is analyzed in order to allow for a more realistic picture of future hydropower planning. The results of this study indicate that, different degrees of future alterations in river discharge and the spatial and temporal distributions of water resources have to be expected, leading to an increase of 7.7%–15.6% in hydropower potentials under the scenario of RCP2.6, RCP4.5 and RCP8.5.

Using multiple satellite-gauge merged precipitation products ensemble for hydrologic uncertainty analysis over the Huaihe River basin

Global satellite–gauge merged precipitation (SGMP) products combine the advantages of satellite precipitation estimates with rain gauge data, providing great potential to hydrological applications. However, the inaccuracies of the precipitation products together with hydrologic model limitations, could cause great uncertainty in streamflow predictions. Therefore, this study investigates the hydrological value of three mainstream global SGMP products, including the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7 product, the Climate Prediction Center (CPC) MORPHing technique (CMORPH) satellite–gauge merged product (CMORPH BLD), the Global Satellite Mapping of Precipitation (GSMaP) Gauge-calibrated product (GSMaP Gauge). They are used as the precipitation input of the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin in China. To better quantify their effects on parameter calibration and streamflow predictions, a newly developed residual error model accompanied with the Bayesian uncertainty analysis are performed. CMORPH satellite-gauge merged precipitation product, recently developed by the China Meteorological Administration (CMA) (CMORPH CMA), is a high-quality regional precipitation product. Thus, this study applies the CMORPH CMA within the same framework to provide a benchmark. The results show that the parameter uncertainty are influenced significantly by the input of various precipitation products. There is a tradeoff between the deterministic streamflow performance and the probabilistic predictive performance for selecting the best input among the three global precipitation products. The streamflow uncertainty intervals of the three global precipitation products are then merged using the Bayesian Model Averaging (BMA) method. The BMA results show satisfying hydrological performance in terms of deterministic streamflow predictions, with the largest Nash-Sutcliffe coefficient of Efficiency (NSCE) values of 0.86 and 0.64, and the smallest absolute relative error (RE) values of 0% and 10.2% in the calibration and validation periods, respectively. In addition, the BMA results also produce much more reliable probabilistic predictions, which even outperform the outcomes of the high-quality CMORPH CMA. Our study demonstrates the potential uncertainty of various SGMP products for model calibration and streamflow predictions. The hydrologic ensemble using multiple global SGMP products provides a promising and advantageous approach to support water management and decision making, especially in ungauged basins.

On the Causes of Declining Colorado River Streamflows

AbstractThe Colorado River is the primary surface water resource in the rapidly growing U.S. Southwest. Over the period 1916–2014, the Upper Colorado River Basin naturalized streamflow declined by 16.5%, despite the fact that annual precipitation in the UCRB over that period increased slightly (+1.4%). In order to examine the causes of the runoff declines, we performed a set of experiments with the Variable Infiltration Capacity hydrology model. Our results show that the pervasive warming has reduced snowpacks and enhanced evapotranspiration over the last 100 years; over half (53%) of the long‐term decreasing runoff trend is associated with the general warming. Negative winter precipitation trends have occurred in the handful of highly productive subbasins that account for over half of the streamflow at Lee's Ferry. We also compared a midcentury drought with the (ongoing) post‐Millennium Drought and find that whereas the earlier drought was caused primarily by pervasive low‐precipitation anomalies across UCRB, higher temperatures have played a large role in the post‐Millennium Drought. The post‐Millennium Drought has also been exacerbated by negative precipitation anomalies in several of the most productive headwater basins. Finally, we evaluate the UCRB April–July runoff forecast for 2017, which decreased dramatically as the runoff season progressed. We find that while late winter and spring 2017 was anomalously warm, the proximate cause of most of the forecast reduction was anomalous late winter and early spring dryness in UCRB, which followed exceptionally large (positive) early winter precipitation anomalies.

The influence of two land-surface hydrology schemes on the regional climate of Africa using the RegCM4 model

Two 12-year simulations were conducted with the RegCM4 model to study how different hydrology schemes can affect the terrestrial hydrology cycle, the surface energy balance, and the regional climate of Africa and in particular tropical Africa. One simulation used the default TOP hydrology scheme in the CLM4.5 land surface model; the other used the variable infiltration capacity (VIC) hydrology model coupled to CLM4.5. The results show that the VIC scheme has a lower soil infiltration rate and hence lower surface soil moisture (10 cm in this study) relative to the default TOP scheme. This leads to a different partitioning of terms in the surface energy balance, with low evapotranspiration and high sensible heat flux, resulting in a net warming effect. The VIC simulation also has low relative humidity due to the low evapotranspiration rate. The low infiltration rate of the VIC hydrology also results in accumulation of moisture on the soil surface. In addition, the VIC scheme generates more precipitation, especially in the summer (JJA) season. Thus, the hydrology parameterization can affect not just the terrestrial hydrology cycle but also energy balance partitioning and hence the surface climate. Moreover, the VIC simulation has smaller biases in the surface energy flux and other surface climate variables in comparison with the default CLM4.5 run. We conclude that the VIC land surface hydrology scheme succeeds in controlling the infiltration rate, the surface soil moisture, and hence total evapotranspiration, which improves the surface energy balance and hence produces a better surface climate. Thus, we recommend the VIC hydrology scheme for future climate studies over Africa.

Hydrologic assessment of the TMPA 3B42-V7 product in a typical alpine and gorge region: the Lancang River basin, China

Abstract To evaluate the accuracy and applicability of the TMPA 3B42-V7 precipitation product for the Lancang River basin, we used different statistical indices to explore the performance of the product in comparison to gauge data. Then, we performed a hydrologic simulation using the Variable Infiltration Capacity (VIC) hydrological model with two scenarios (Scenario I: streamflow simulation using gauge-calibrated parameters; Scenario II: streamflow simulation using 3B42-V7-recalibrated parameters) to verify the applicability of the product. The results of the precipitation analysis show good accuracy of the V7 precipitation data. The accuracy increases with the increase of both space and time scales, while time scale increases cause a stronger effect. The satellite can accurately measure most of the precipitation but tends to misidentify non-precipitation events as light precipitation events (<1 mm/day). The results of the hydrologic simulation show that the VIC hydrological model has good applicability for the Lancang River basin. However, 3B42-V7 data did not perform as well under Scenario I with the lowest Nash–Sutcliffe coefficient of efficiency (NSCE) of 0.42; Scenario II suggests that the error drops significantly and the NSCE increases to 0.70 or beyond. In addition, the simulation accuracy increases with increased temporal scale.

Seasonal streamflow forecasts for Europe – Part I: Hindcast verification with pseudo- and real observations

Abstract. Seasonal predictions of river flow can be exploited among others to optimise hydropower energy generation, navigability of rivers and irrigation management to decrease crop yield losses. This paper is the first of two papers dealing with a physical model-based system built to produce probabilistic seasonal hydrological forecasts, applied here to Europe. This paper presents the development of the system and the evaluation of its skill. The variable infiltration capacity (VIC) hydrological model is forced with bias-corrected output of ECMWF's seasonal forecast system 4. For the assessment of skill, we analysed hindcasts (1981–2010) against a reference run, in which VIC was forced by gridded meteorological observations. The reference run was also used to generate initial hydrological conditions for the hindcasts. The skill in run-off and discharge hindcasts is analysed with monthly temporal resolution, up to 7 months of lead time, for the entire annual cycle. Using the reference run output as pseudo-observations and taking the correlation coefficient as metric, hot spots of significant theoretical skill in discharge and run-off were identified in Fennoscandia (from January to October), the southern part of the Mediterranean (from June to August), Poland, northern Germany, Romania and Bulgaria (mainly from November to January), western France (from December to May) and the eastern side of Great Britain (January to April). Generally, the skill decreases with increasing lead time, except in spring in regions with snow-rich winters. In some areas some skill persists even at the longest lead times (7 months). Theoretical skill was compared to actual skill as determined with real discharge observations from 747 stations. Actual skill is generally substantially less than theoretical skill. This effect is stronger for small basins than for large basins. Qualitatively, the use of different skill metrics (correlation coefficient; relative operating characteristics, ROC, area; and ranked probability skill score, RPSS) leads to broadly similar spatio-temporal patterns of skill, but the level of skill decreases, and the area of skill shrinks, in the following order: correlation coefficient; ROC area below-normal (BN) tercile; ROC area above-normal (AN) tercile; ranked probability skill score; and, finally, ROC near-normal (NN) tercile.