Initial Soil Moisture Conditions Research Articles

Assessing crop yield and water balance in crop rotation irrigation systems: Exploring sensitivity to soil hydraulic characteristics and initial moisture conditions in the North China Plain

Multiple cropping is an effective measure to enhance the intensity of land use. The North China Plain is one of China’s most important grain production areas, with 70 % of the arable land under double rotation of winter wheat and summer maize. The allocation of irrigation water between two crop seasons depends on soil water flow and crop water consumption. This is because the amount of moisture left in the soil at the end of one season affects how much moisture is in the soil at the beginning of the next season. As a result, the amount of crops produced and the amount of water needed for irrigation are influenced by the initial soil moisture conditions and the soil’s hydraulic properties. This study aims to analyze how various factors affect crop yield when faced with water scarcity. The factors considered include initial soil moisture condition, soil texture, and irrigation scheduling. The simulation results indicate that, in most cases, initial soil moisture conditions have a more significant impact on crop yield than soil hydraulic characteristics. The impact of irrigation can differ based on the irrigation method and availability of water. Hence, when distributing irrigation water over a year, it is crucial to consider the soil’s water transport between two crop cycles to achieve the ideal full and deficit irrigation in a crop rotation system. Additionally, a joint optimal irrigation plan can significantly reduce the adverse effects of unfavorable soil hydraulic characteristics. Moreover, the optimal irrigation strategy can enhance crop water productivity and food security simultaneously.

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.

Skillful seasonal prediction of the 2022–23 mega soil drought over the Yangtze River basin by combining dynamical climate prediction and copula analysis

An unprecedented soil moisture drought broke out over the Yangtze River basin (YRB) in the summer of 2022 and lasted until the spring of 2023, caused great economic losses and serious environmental issues. With the rapid onset and long-lasting duration, the mega soil drought challenges the current seasonal prediction capacity. Whether the state-of-the-art climate models provide skillful predictions of the onset, persistence and recovery of the 2022–23 mega soil drought needs to be assessed. Identified by the drought area percentage, here we show that the mega soil drought over the YRB started from July, 2022, reached the peak in August, and diminished in April, 2023. Combined with real-time predictions of monthly precipitation released by three climate models participating in the North American multi-model ensemble (NMME) project, we predict the monthly evolution of the 2022–23 soil drought through a joint distribution between precipitation and soil moisture established by the copula method. The results indicate that the NMME/copula prediction well reproduced the spatiotemporal evolution of the mega soil drought at 1 month lead. Using the climatological prediction that relies on the information of initial soil moisture conditions as the reference forecast, the Brier skill score (BSS) values for NMME multi-model ensemble are 0.26, 0.23 and 0.2 for the forecast lead times increased from 1 to 3 months during the entire soil drought period. Specifically, the BSS is 0.14 at 2 months lead during drought onset stage, and 0.26 at 3 months lead during persistence stage, while it is close to zero at all leads during the recovery stage. Our study implies that climate models have great potential in probabilistic seasonal prediction of the onset and persistency of mega soil drought through combining with the copula method.

Runoff generation in a semiarid environment: The role of rainstorm intra-event temporal variability and antecedent soil moisture

Rainfall intensity and antecedent soil moisture are key variables affecting the initiation and accumulation of runoff, and therefore, impact on the occurence flood events. We used time series of rainfall intensities characterizing rainstorms with different mean, standard deviation, and skewness to simulate runoff response of a sealed loamy soil profile under various initial soil moisture conditions. We found that shifting from wet to dry initial soil moisture leads to a 300 % increase in ponding time and a 350 % decrease in total runoff. Intense rainfall events catalyze runoff development and runoff occurs earlier with increasing mean, maximum intensity, and variance of rainfall. Higher variance in intra-event storm-intensity temporal distribution yields more runoff. Earlier runoff formation aligned with negatively skewed storm structures, but largest cumulative runoff resulted from storms displaying near-zero skewness values. The combination between rainfall intensification and extended dry periods between storms might reduce potential runoff. These insights improve our understanding of anticipated impacts of climate variations on floods and may also contribute to ecosystem health evaluations, and bolster predictive capabilities of surface processes.

Evaluation of Soil Moisture in the Canadian Seasonal to Interannual Prediction System, Version 2.1 (CanSIPSv2.1)

Abstract We evaluate the soil moisture hindcasts and the reconstruction runs giving the hindcasts initial conditions in version 2.1 of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2.1). Different strategies are used to initialize the hindcasts for the two CanSIPSv2.1 models, CanCM4i and the coupled Global Environmental Multiscale, version 5.1, (GEM5)–NEMO model (GEM5-NEMO), with contrasting impacts on the soil moisture initial conditions and forecast performance. Forecast correlation skill is decomposed into contributions from persistence of the initial anomalies and contributions not linked to persistence, with performance largely driven by the accuracy of the initial conditions in regions of strong persistence. Seasonal soil moisture correlation skill is significant for several months into the hindcasts depending on initial and target months, with contributions not linked to persistence becoming more notable at longer lead times. For the first 2–4 months, the quality of CanSIPSv2.1 ensemble mean forecasts tends to be higher on average during summer and fall and is comparable to that of the best performing model, whereas CanSIPSv2.1 outperforms the single models during spring and winter. For longer lead times, remote climate influences from the Pacific Ocean are notable and contribute to predictable soil moisture variability in teleconnected regions.

A Study on C-band Synthetic Aperture Radar Soil Moisture Estimation Based on Machine Learning Using Soil Physics, Topography, and Hydrological Information

In this study, we applied machine learning to estimate soil moisture levels in South Korea by harnessing data from the Sentinel-1 C-band synthetic aperture radar (SAR). Our approach incorporated not only the relationship between backscattering coefficients and soil moisture but also diverse physical characteristics. This encompassed topographic information, soil physics data, and antecedent precipitation which is a hydrological factor influencing the initial condition of soil moisture. We applied a variety of machine-learning techniques and conducted a comprehensive analysis to compare the performance of each model.

Experimental analysis to assess the hydrological efficiency and the nutrient leaching behavior of a new green wall system

Green Walls represent a sustainable solution to mitigate the effects due to climate change and urbanization. However, although they have been widely investigated in different fields of science, studies on the potential of these systems to manage urban stormwater are still few. Moreover, even if these systems provide multiple benefits, as other nature-based solutions, they leach nutrients due to growing media, decomposed vegetation, and the possibility of fertilizer use. In this regard, several studies have evaluated the nutrient concentrations in the runoff from green roofs, while studies that have analyzed the nutrient-leaching behavior of green walls are still limited. To bridge these scientific gaps, this study presents experimental findings on the hydrological efficiency and nutrient-leaching behavior of an innovative modular living wall system. Some rainfall-runoff tests were carried out to assess the hydrological response of a new green wall system in retaining stormwater. To evaluate the concentration of the nutrients, the collected outflow was analyzed by spectrophotometer UV–visible. The findings show that the developed green wall panel presents good retention capacity by considering different simulated rainfalls and varying the initial soil moisture conditions. The results in terms of nutrient concentrations highlight that the vegetation life cycle and the fertilizer uses affect the quality of the water released from the green wall panel. The concentration of the analyzed nutrients is influenced by the simulated rainfall's hydrological characteristics and the days between the planting phase and the test. However, the overall results show that the concentrations of each analyzed nutrient are low, except after the fertilizer use, highlighting that the choice of vegetation that does not need external nutrients should be preferred during the design of a green wall.

Soil moisture–precipitation feedbacks in pre‐ and post‐monsoon landfalling tropical cyclones in Bay of Bengal

AbstractThe Bay of Bengal (BoB) experiences an average of three to four tropical cyclones (TCs) annually. The high population density of surrounding countries often leads to disastrous consequences when a TC makes landfall. As a result, it is critical to understand the evolution and intensity of rainfall associated with a TC that originates in the BoB. In this study, we examine the impact of initial soil moisture (SM) conditions on the TC track, TC recycled precipitation, and other TC variables using the Weather Research and Forecasting (WRF) model upgraded with Eulerian water‐tagging capabilities. We simulated pre‐monsoon TCs Amphan, Titli, Viyaru and post‐monsoon cyclones Phailin, Titli and Helen originating in the BoB. We conducted sensitivity experiments with dry and wet initial SM conditions to determine the impact of initial SM changes on TCs. We also generated four control simulations for each TC by changing the initial time to assess the effect of internal model variability. Our results indicate that initial SM conditions impact TC more than the internal model variability. We find that changes in the initial SM affect the latent heat flux, which influences the temperature and the synoptic wind pattern over the entire domain, resulting in changes in the TC properties. We find the feedback of SM to TC precipitation (quantified as recycled precipitation) is stronger as the TC approaches the landfall. The post‐landfall recycling ratio for pre‐monsoon TCs is approximately 5%–10%, but is around 20%–30% for post‐monsoon TCs. We observe that the Viyaru, Titli and Helen TC tracks are more sensitive to the initial SM conditions compared to the other three TCs. In addition to SM, we find that factors such as proximity to land, and TC intensity also have a role in determining the quantity of recycled precipitation for a TC.

Repeated falling-head method for in situ measurements of saturated hydraulic conductivity using a single cylinder

A simple, repeated falling-head (RFH) method, which uses an inexpensive portable cylinder to quickly determine field-saturated hydraulic conductivity (Kfs), is presented. A cylinder of radius r, inserted vertically from the soil surface to a depth d, is used as a water supply tank, through which water infiltrates into the soil. The falling-head test is repeated without allowing the cylinder to be drained entirely to eliminate the effects of the initial soil moisture conditions. Either change in the water level (H) in the water supply cylinder or strong linearity between the infiltration flux (qs) and H can be used to determine Kfs directly or by multiplying the slope with an empirical ring-installation scaling length, Lg; thus, no soil-dependent variable is necessary. To obtain the Lg value for various conditions, we carried out numerical experiments using HYDRUS (2D/3D) with a recently implemented reservoir boundary condition for six different soil textures, ranging from coarse soil (e.g., sand) to fine soil (e.g., silty clay loam), and two different ranges of water levels, 15 ≤ H ≤ 25 cm and 2 ≤ H ≤ 6 cm. Numerical results showed that the Lg has a strong linear dependence on d and r, where Lg increases as d and r increase. We propose a new linear model to determine Lg with optimized coefficients for each H range. Numerical results showed no significant differences in the estimated Kfs after the second repetition, confirming that repeating the falling head test twice is sufficient. The newly obtained Lg values were then applied to the experimental data obtained at multiple fields having different soil textures. The Kfs values determined using the RFH method agreed well with those measured using the field two-ponding depths steady-state method and/or the FH method in the lab. These results demonstrate the reliability of the proposed RFH method.

Improving the Soil Moisture Initial Conditions of Hydrological Model with Reanalysis Soil Moisture Data

Improving the Soil Moisture Initial Conditions of Hydrological Model with Reanalysis Soil Moisture Data

Initial soil moisture conditions affect the responses of colloid mobilisation and associated cadmium transport in opposite directions

The effects of initial soil moisture on colloid-associated transport are still poorly understood given the well-recognized significance of colloid-facilitated transport of strongly-sorbing contaminants. In this study, Cd leaching was sequentially conducted in an intact soil column under three initial moisture conditions (near saturation, field capacity and dryness). Soil colloids were always the dominant carriers for Cd. However, upon the lowering of initial soil moisture, increased transport of colloids (96.2→101.0→168.2 mg) was observed, surprisingly, along with decreased transport of colloid-associated Cd (C-Cd) (23.9→10.7→8.2 µg) and enrichment factor (248.4→105.9→48.8 mg/kg) of Cd on colloids, resulting from pH reduction which increased Cd desorption and colloid size increase and/or ζ-potential decrease that showed lower affinity for Cd. Correlation, redundancy analysis and structural equation modelling revealed the dominantly positive role of colloids, EC plus cations (Ca2+ and Mg2+) in the release of C-Cd and dissolved Cd (D-Cd), respectively, under initial moistures of near saturation and field capacity. Under initially dry conditions, soil water potential showed dominantly negative effects on the transport of both C-Cd and D-Cd. These findings highlighted the critical role of initial moisture conditions in modulating colloid-facilitated Cd mobilisation, providing insights into the environmental risk assessment of heavy metals in other leaching scenarios.

Influence of ASCAT soil moisture on prediction of track and intensity of landfall tropical cyclones

ABSTRACT The current study attempted to evaluate the impact of Soil Moisture (SM) initial conditions in a regional NWP system on the simulation of land falling cyclones over North Indian Ocean region. SM initial conditions used in this study are created using a simplified EKF based LDAS, in which satellite derived SM information is also used. Here, two sets of numerical experiments using regional NWP system are performed with two different sets of SM initial conditions. The CTL (assimilated only surface level observations in LDAS) and ASCAT (assimilated satellite derived SM plus observations used in CTL) experiments are performed to understand the impact of SM initial conditions in NCUM-R NWP system. The atmospheric initial conditions for both experiments are prepared through 4DVAR assimilation technique. This study shows that high resolution regional model initialized with improved SM initial conditions created using satellite observations could improve structure, intensity, track and evolution of the storms. The positive values of humidity Jacobians are noticed over the regions affected by storms mainly in ASCAT. The evolution of vorticity tendency and convergence profiles is well differentiated in ASCAT as the system moved from higher to lower intensity stage or vice versa, but that pattern is not observed in CTL. The value of static stability indices is varying with strength of cyclones, which are well represented in ASCAT and are also well matched with observations. The evolution of magnitude of diabatic heating in and around the storm core region is more realistic in ASCAT than CTL. The moisture budget terms are improved in ASCAT, the contribution of moisture convergence (evaporation) to the precipitation is more over the oceanic (land) region before and after landfall of storm. The study deduced that accurate SM initial conditions are essential for better prediction of structure and intensity of high impact weather events.

Modeling management of continuous dryland cotton with an intervening winter wheat cover crop in a semiarid climate

Although winter cover crop residue can mitigate the stresses of dryland production in semi-arid regions, cover crops can also reduce soil moisture and cash crop yields. In some field studies of dryland cotton grown after terminated winter wheat in the U.S. Southern High Plains (SHP) and Texas Rolling Plains cotton yields were increased relative to continuous cotton, while others had no significant yield or soil water effect. These uncertain outcomes may be due to the trial's limited sampling of seasonal rainfall conditions. To estimate the probabilities of cover crop effects under more representative SHP climate conditions, 294 station-years of crop model simulations of terminated winter wheat followed by dryland cotton were conducted. These simulations were driven by weather data from 21 SHP weather stations during 2005–2019. Each station-year's simulations were repeated under 54 combinations of wheat planting, termination, and cotton planting dates, 2 soil series with different water capacities, and 10 initial soil moisture conditions. When simulations begin with fall soil moisture at field capacity optimal management options for both soils plant wheat early and cotton late, but have different wheat termination dates. Before cotton planting winter cover crop effects are dominated by reduced surface evaporation and increased transpiration, with greater transpiration effects producing decreased column soil moisture (CSM) at wheat termination. Some soil moisture recharge occurs between termination and cotton planting, but cover crops reduce CSM at cotton planting in both soils in ~75% of simulations. Reduced soil evaporation and soil moisture recovery continues after cotton planting, resulting in positive effects on seed cotton yield in 50% of the silty clay loam simulations and in 67% of the fine sandy loam simulations. Gradually reducing initial fall soil moisture in the silty clay loam reduces wheat biomass but increases the incidence of positive effects on seed cotton yields and CSM at cotton planting and harvest. By contrast, drier initial soil moisture in the fine sandy loam had relatively minor yield and CSM effects. In both soils terminated wheat residue led to increased CSM at cotton harvest in at least 70% of the simulations regardless of soil moisture at wheat planting.

Skill and sources of skill in seasonal streamflow hindcasts for South America made with ECMWF’s SEAS5 and VIC

The first aim of the present paper is the determination of the magnitude, annual variation and spatial distribution of skill in seasonal hindcasts of runoff and discharge in the entire continent of South America. We evaluated 35 years of hindcasts generated with the Variable Infiltration Capacity (VIC) hydrological model forced with SEAS5 hindcasts. Initial conditions of terrestrial water and so-called pseudo-observations were computed with a reference (i.e. historic) simulation. Skill was determined with monthly temporal resolution for the entire annual cycle and mostly using the pseudo-observations for verification. The second aim of the paper is the explanation of skill in terms of its sources, namely meteorological forcing and the initial conditions. Therefore, two sets of restricted hindcasts, which isolate the sources of skill, were analysed. The SEAS5 precipitation hindcasts exhibit significant skill even at the longest lead times (7 months). Beyond the first lead month we found significant skill in 13–43 % of the grid cells, depending on target and lead month. Levels of skill are higher in the full hindcasts (significant skill in 31–89 % of the grid cells). At the continental scale more of the skill is caused by the forcing than by the initial conditions. The runoff hindcasts are skilful in large parts of the continent. In a 1000 km wide band along the north coast of the continent and in southeast South America, most of the skill is due to the forcing. A typical feature of these regions is an increase of skill with lead time during specific parts of the year, which is against the common tendency. In Argentina and north Chile most of the skill in the runoff hindcasts can be attributed to the initial conditions of soil moisture. Verification with real observations of discharge broadly confirmed the skill pattern obtained with pseudo-observations.

ANALISIS KEMAMPUAN SISTEM IRIGASI TETES BERTINGKAT DALAM PEMBERIAN LENGAS TANAH PADA POLYBAG

In increasing the supply of food in residential areas, it is necessary to encourage the use of land and water sources in the yard even though the land area is limited. The design of multilevel drip irrigation may be an option in these housings, and therefore it is necessary to test and determine the ability of the irrigation to discharge, uniformity and soil moisture produced. This study aims to determine the effect of using inch PVC pipe as a secondary network on discharge, uniformity (CU) and soil moisture (w) in a multilevel drip irrigation system. Experiments were carried out with a 150 liter reservoir water source 3 m high, soil moisture test with a test duration of 5 minutes, 10 minutes and 15 minutes. Data analysis was carried out on discharge data (Q), irrigation volume and soil moisture. The research results are presented in tables, graphs and concluded descriptively. The results showed that the secondary pipe flow rate was Q1 822.54 cm3/sec, Q2 107.47 cm3/sec and Q3 15.39 cm3/sec. Irrigation uniformity in TSK irrigation operations obtained CU of 72.67% and in SK obtained CU of about 51.49% to 89.34%. Soil moisture produced at a duration of 5 minutes, 10 minutes and 15 minutes with an initial soil moisture condition range of 14%-28%, the results on the 1st floor (w1) ranged from 41%-50%, for the second floor w2 it was around 31%-45 % and on the third floor w3 around 25%-40%

Preferential flow patterns in forested hillslopes of east Tibetan Plateau revealed by dye tracing and soil moisture network

AbstractPreferential flow (PF) through soil and regolith results in a rapid vertical and lateral water movement within the profile. This study focused on quantifying PF in contrasting forested hillslopes of the Hailuo Valley, located on China's east Tibetan Plateau. Quantifying PF in this region is challenging since the underlying matrix is complex, with shallow soils, thick underlying saprolite, and the combined effect of moraines and weathered residual material. We developed new methods that integrated dye tracing with a high‐frequency soil moisture monitoring network to characterise PF pathways and quantity PF frequency on contrasting forested hillslopes (coniferous and broadleaved). Dye tracing experiments showed that soil‐root interfaces in the upper soil layer (10–50 cm) and soil‐rock interfaces in the deeper soil layer (50–100 cm) were the primary PF pathways and that large rocks strongly influence the percolation depth of water. The high‐frequency soil moisture network revealed that the mean PF frequency was 67.8% and 71.7% in the coniferous and broadleaved forests, respectively. The frequency of PF in the deeper soil layer increased from upslope to the downslope locations on both forested hillslopes, highlighting the tendency for PF to occur downslope. In addition to matrix conditions (e.g., stony saprolite soil), the total amount and maximum intensity of precipitation (as throughfall in this study) were identified as factors that control PF occurrence. In contrast, the initial soil water conditions (at 10, 50 and 100 cm depth) were insignificant in predicting PF occurrence. Results of this field‐based study highlight that PF is a ubiquitous and critical subsurface flow mechanism that regulates rainfall‐runoff relationships in forests of the Tibetan Plateau, underscoring the need to consider PF in hillslope hydrological modelling.Highlights Combined dye tracing and soil moisture monitoring network were applied to explore PF on forested hillslopes. Root networks and rock fragments constituted the main PF paths. PF frequency increased from upslope to downslope in two forest types. Initial soil moisture conditions showed no controlling effect on PF occurrence.

The Climatic Role of Interactive Leaf Phenology in the Vegetation- Atmosphere System of Radiative-Convective Equilibrium Storm-Resolving Simulations

Storm-resolving simulations where deep convection can be explicitly resolved are performed in the idealized radiative-convective equilibrium framework to explore the climatic role of interactive leaf phenology. By initializing the system with different initial soil moisture and leaf area index (LAI) conditions, we find three categories of potential equilibrium climatic and vegetation states: a hot desert planet without vegetation, an intermediate sparsely vegetated planet, and a wet fully vegetated planet. The wet fully vegetated equilibrium category occurs over the widest range of initial soil moisture as it occurs as soon as soil saturation is 19% higher than the permanent wilting point (35%). This indicates that a quite harsh environment is needed in our modeling system to force leaves to be shed. The attained equilibrium states are only dependent upon the initial soil moisture, not the initial LAI. However, interactive leaves do allow an earlier transition from the intermediate to the wet vegetated equilibrium category. Hence, interactive leaves make the vegetation-atmosphere system more stable and more resilient to drying. This effect could be well approximated by just prescribing the LAI to its maximum value. Finally, our sensitivity experiments reveal that leaves influence the climate equally through their controls on canopy conductance and vegetation cover, whereas albedo changes play a negligible role.

The long-standing dilemma of European summer temperatures at the mid-Holocene and other considerations on learning from the past for the future using a regional climate model

Abstract. The past as an analogue for the future is one of the main motivations to use climate models for paleoclimate applications. Assessing possible model limitations in simulating past climate changes can lead to an improved understanding and representation of the response of the climate system to changes in the forcing, setting the basis for more reliable information for the future. In this study, the regional climate model (RCM) COSMO-CLM is used for the investigation of the mid-Holocene (MH, 6000 years ago) European climate, aiming to contribute to the solution of the long-standing debate on the reconstruction of MH summer temperatures for the region, and gaining more insights into the development of appropriate methods for the production of future climate projections. Two physically perturbed ensembles (PPEs) are first built by perturbing model physics and parameter values, consistently over two periods characterized by different forcing (i.e., the MH and pre-industrial, PI). The goal is to uncover possible processes associated with the considered changes that could deliver a response in MH summer temperatures closer to evidence from continental-scale pollen-based reconstructions. None of the investigated changes in model configuration produces remarkable differences with respect to the mean model behavior. This indicates a limited sensitivity of the model to changes in the climate forcing, in terms of its structural uncertainty. Additional sensitivity tests are further conducted for the MH, by perturbing the model initial soil moisture conditions at the beginning of spring. A strong spatial dependency of summer near-surface temperatures on the soil moisture available in spring is evinced from these experiments, with particularly remarkable differences evident over the Balkans and the areas north of the Black Sea. This emphasizes the role of soil–atmosphere interactions as one of the possible drivers of the differences in proxy-based summer temperatures evident between northern and southern Europe. A well-known deficiency of the considered land scheme of COSMO-CLM in properly retaining spring soil moisture, confirmed by the performed tests, suggests that more attention should be paid to the performance of the soil component of climate models applied to this case study. The consideration of more complex soil schemes may be required to help bridging the gap between models and proxy reconstructions. Finally, the distribution of the PPEs with changes in model configuration is analyzed for different variables. In almost all of the considered cases the results show that what is optimal for one period, in terms of a model configuration, is not the best for another characterized by different radiative forcing. These results raise concerns about the usefulness of automatic and objective calibration methods for RCMs, suggesting that a preferable approach is the production of small PPEs that target a set of model configurations, properly representing climate phenomena characteristic of the target region and that will be likely to contain the best model answer under different forcing.

Hydrometeorological analysis of the 12 and 13 September 2019 widespread flash flooding in eastern Spain

Abstract. On 12 and 13 September 2019, a long-lasting heavy precipitation episode (HPE) affected the València, Murcia and Almería regions in eastern Spain. Observed rainfall amounts were close to 500 mm in 48 h, being the highest cumulative precipitation registered in some rain gauges for the last century. Subsequent widespread flash flooding caused seven fatalities and estimated economical losses above EUR 425 million. High-resolution precipitation estimates from weather radar observations and flood response from stream gauges are used in combination with a fully distributed hydrological model to examine the main hydrometeorological processes within the HyMeX programme. This HPE was characterized by successive, well-organized convective structures that impacted a spatial extent of 7500 km2, with rainfall amounts equal to or larger than 200 mm. The main factors driving the flood response were quasi-stationarity of heavy precipitation, very dry initial soil moisture conditions and large storage capacities. Most of the examined catchments exhibited a dampened and delayed hydrological response to cumulative precipitation: until runoff thresholds were exceeded, infiltration-excess runoff generation did not start. This threshold-based hydrological behaviour may impact the shape of flood peak distributions, hindering strict flood frequency statistical analysis due to the generally limited lengths of data records in arid and semi-arid catchments. As an alternative, a power-law relationship is analytically derived to specifically link flood magnitude to rainfall amount, with the parameters depending on basin and precipitation features. This power law could aid in developing empirical envelope curves so as to assess hydrologic risk in arid and semi-arid catchments with a threshold-based hydrological behaviour.

Improving the prediction of monsoon depressions by assimilating ASCAT soil moisture in NCUM-R modeling system

The present study investigates the impact of assimilation of satellite derived soil wetness data from Advanced Scatterometer (ASCAT) on simulation of inland moving monsoon depressions (MDs) over Indian region using high resolution NCUM-R forecasting system. The simplified Extended Kalman Filter (sEKF) based Land Surface Data Assimilation (LSDA) system is used to create land surface soil moisture initial conditions for NCUM-R by assimilating ASCAT soil moisture (SM) along with screen level observations. Two numerical experiments, namely CTL (incorporating only screen level observations in LSDA) and ASCAT (assimilating both ASCAT SM and screen level observations in LSDA) are carried out to update the model soil moisture initial conditions. Identical atmospheric initial condition prepared considering the 4DVAR data assimilation technique is used in both experiments.The results of this study show that the assimilation of remotely sensed SM has a beneficial impact on MD simulation, its movement, structure and associated precipitation. The analysis increment of fluxes from ASCAT experiment clearly shows properly coupled positive feedback between land and atmosphere. SM in the vicinity of MD is considerably improved in the ASCAT analysis as compared to the CTL analysis and is well correlated with the observed rainfall over the regions. The root mean square error of top layer SM is decreased by 5 to 15% in ASCAT analyses compared to CTL analyses. The land-atmosphere coupling feedback is investigated by using Dirmeyer's indices, it is noticed that the precipitation modulated by the latent heat flux is higher in ASCAT simulation than in the CTL simulation. This improvement is due to the proper representation of surface conditions by assimilating the satellite SM observations into LSDA. The contribution of individual terms of vorticity equation and total vorticity tendency is considerably well represented in ASCAT experiment as compared to the CTL experiment during the various phases of MD. Overall, this study indicates that the use of ASCAT SM in the preparation of soil moisture initial conditions helps to improve the forecast of MDs by the regional NWP system.