Spatial pattern oriented multicriteria sensitivity analysis of a distributed hydrologic model

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represent an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity typically do not reflect other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). The Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definitions based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis

Low flows: mechanisms, forecasts and climate change impacts

A research on low flows may seem controversial for a “wet” country protected by dykes and barriers. However, low flows in dry summers such as in 1976, 1985 and 2003 indicate that it may happen also in the Rhine basin. Improved medium-range and seasonal low fow forecasts are important as there is an increasing interest to account for low flow forecasts in decision support systems, e.g. how to operate river navigation and power plants during low flow periods to maximize the gain. In this thesis, dominant low flow mechanisms in the Rhine basin are identified. These mechanisms are used to select two appropriate conceptual models for 10 day and 90 day ahead low flow forecasts. Moreover, the identified temporal scales of the dominant low flow mechanisms are used to develop two data-driven seasonal models. The effects of major uncertainty sources on low flow forecasts are assessed using Monte Carlo techniques. Parameter uncertainty is found to have the largest effect on 10 day low flow forecasts, whereas ensemble seasonal precipitation forecasts has the largest effect on 90 day low fow forecasts. Climate change impacts on the seasonality of low flows are assessed using the outputs of an ensemble of climate models to run a hydrological model. By 2063-2098, significant changes are expected in the seasonality of low flows in the Rhine basin

A Novel Surgical Reconstruction Technique in the Management of Chronic Ulnar Collateral Ligament Tears with Volar Subluxation

Background: We hypothesized that ulnar collateral ligament reconstruction is inadequate for metacarpophalangeal joint stabilization in chronic ulnar collateral ligament injuries with volar subluxation due to dorsal joint capsule injury. We consecutively performed both ulnar collateral ligament and dorsal joint capsule reconstruction to treat patients with a chronic ulnar collateral ligament tear with volar subluxation. This study aimed to present our preliminary results and experience with this technique in managing such cases

Effect of Dynamic PET Scaling with LAI and Aspect on the Spatial Performance of a Distributed Hydrologic Model

The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on the soil properties and crop-vegetation dynamics. Mostly coarse-scale meteorological forcing is used to estimate only the water balance at the catchment outlet. The mesoscale Hydrologic Model (mHM) is one of the rare models that incorporate remote sensing data, i.e., leaf area index (LAI) and aspect, to improve the actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduce a new weight parameter, “alphax”, that allows the user to incorporate both LAI and aspect together for potential evapotranspiration (PET) scaling. With the mHM code enhancement, the modeler also has the option of using raw PET with no scaling. In this study, streamflow and AET are simulated using the mHM in The Main Basin (Germany) for the period of 2002–2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using the Optimization Software Toolkit (OSTRICH). For calibration and evaluation, the KGE metric is used for water balance, and the SPAEF metric is used for evaluating spatial patterns of AET. Our results show that the AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. This is key for agronomic studies like crop yield estimations and irrigation water use. The additional “alphax” parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain

The Effect of Postoperative Mild Varus Deformity on Functional Outcome Scores after Primary Total Knee Arthroplasty in Patients with Varus Osteoarthritis

Introduction: This study evaluated the effect of both postoperative residual varus alignment and the amount of correction in lower limb alignment (LLA) on postoperative functional outcomes of total knee arthroplasty TKAs in patients with preoperative varus deformity

Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated patterns. To address this, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as a modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. We apply the mesoscale Hydrological Model (mHM) to model the hydrological cycle of the Senegal River basin. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. As objective functions we applied the Kling-Gupta-Efficiency (KGE) for Q and the Spatial Efficiency (SPAEF) for ET. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial pattern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern, i.e., a 30% decrease in SPAEF. Both calibrations reached comparable performance of Q, i.e., KGE around 0.7. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature

Effect of data length, spin-up period and spatial model resolution on fully distributed hydrological model calibration in the Moselle basin

Subjective decisions in hydrologic model calibration can have drastic impacts on our understanding of basin processes and simulated fluxes. Here, we present a multicase calibration approach to determine three pillars of an appropriate hydrological model configuration, i.e. calibration data length, spin-up period, and spatial resolution, using a spatially distributed meso-scale hydrological model (mHM) together with a dynamically dimensioned search (DDS) algorithm and Nash-Sutcliffe efficiency (NSE) for the Moselle basin. The results show that a 10-year calibration data length, 2-year spin-up period, and 4-km model resolution are appropriate for the Moselle basin to reduce the computational burden while simulating streamflow with a decent performance. Although the calibration data length and spatial resolution are related to the extent and quality of the data, and the spin-up period is basin dependent, analysing the combined effects further allowed us to understand the interactions of these three usually overlooked pillars in the mHM configuration

Mid-term results of hindfoot arthrodesis with a retrograde intra-medullary nail in 24 patients with diabetic Charcot neuroarthropathy

Background and purpose - Hindfoot arthrodesis using retrograde intramedullary nailing assumes a critical role in limb salvage for patients with diabetic Charcot neuro-arthropathy (CN). However, this procedure is compelling and fraught with complications in diabetic patients. We report the mid-term clinical and radiological outcomes of retrograde intramedullary nailing for severe foot and ankle deformity in patients with diabetic CN. Patients and methods - Hindfoot arthrodesis was performed using a retrograde intramedullary nail in 24 patients (15 females) with diabetic Charcot foot. The mean age of the patients was 62 years (33-82); the mean follow-up was 45 months (24-70). The primary outcomes were rates of fusion, limb salvage, and complications. Results - The overall fusion rate was 23/24, and none of the patients needed amputation. The rate of superficial wound infection was 4/24, and no deep infection or osteomyelitis was observed postoperatively. Interpretation - For selected cases of diabetic CN with severe foot and ankle deformity, hindfoot arthrodesis using a retrograde intramedullary nail seems to be a good technique in achieving fusion, limb salvage, and avoidance of complications

Acromion-axillary nerve distance and its relation to the arm length in the prediction of the axillary nerve position: a clinical study

Background Because of the broad anatomic variation in the course of the axillary nerve, several cadaveric studies have investigated the acromion-axillary nerve distance and its association with the humeral length to predict the axillary nerve location. This study aimed to analyze the acromion-axillary nerve distance (AAND) and its relation to the arm length (AL) in patients who underwent internal plate fixation for proximal humerus fractures. Methods The present prospective study involved 37 patients (15 female, 22 male; the mean age = 51 years, age range 19-76) with displaced proximal humerus fractures treated by open reduction and internal fixation. After anatomic reduction and fixation were achieved, the following parameters were measured in each patient before wound closure without making an extra incision or dissection: (1) the distance from the anterolateral edge of the acromion to the course of the axillary nerve was recorded as the acromion-axillary nerve distance and (2) the distance from the anterolateral edge of the acromion to the lateral epicondyle of the humerus was recorded as arm length. The ratio of AAND to AL was then calculated and recorded as the axillary nerve index (ANI). Results The mean AAND was 6 +/- 0.36 cm (range 5.5-6.6), and the mean arm length was 32.91 +/- 2.9 cm (range 24-38). The mean axillary nerve ratio was 0.18 +/- 0.02 (range 0.16 to 0.23). There was a significant moderate positive correlation between AL and AAND (p = 0.006; r = 0.447). The axillary nerve location was predictable in only 18% of the patients. Conclusion During the anterolateral deltoid-splitting approach to the shoulder joint, 5.5 cm from the anterolateral edge of the acromion could be considered a safe zone to prevent possible axillary nerve injury

Long-term results and comparison of the three different high tibial osteotomy and fixation techniques in medial compartment arthrosis

Background: The purpose of this study is to report and analyze the long-term outcomes of the patients who underwent high tibial osteotomy (HTO) with three different techniques for the treatment of medial compartment arthrosis