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• Proactive drought responses are crucial in a drought vulnerable future. • Antecedent conditions need to be considered in context of anticipated conditions. • We combine rainfall, soil moisture and evapotranspiration data with forecasts for early warning. • Validation efforts found promising accuracy in the drought early warning maps. • Proof-of-concept drought early warning system can aid proactive drought management. Droughts are a cyclical feature of Australia's climate that have compounding impacts on agricultural productivity and the wellbeing of drought-affected communities. Understanding anticipated drought conditions in context of antecedent observations is critical to providing early warning of drought. In this study we paired probabilistic seasonal rainfall forecasts with precipitation, soil moisture and evapotranspiration data that were objectively combined using Principal Component Analysis (PCA). The final Drought Early Warning System (DEWS) maps overlay forecasting information with the multi-variate PCA-weighted maps at 1-, 3- and 6-month timescales over the common period of overlap between all datasets (1982–2018). In this study period, the 1982–1983 Ash Wednesday tinder drought and the 1997–2001 Millennium drought were investigated. We validated PCA-weighted maps with satellite vegetation data and found performance was strongest over the Murray Darling Basin region (R = 0.63, p = 0.009) and poorest over Central interior Australia (insignificant correlations). We also validated PCA-weighted maps using agricultural commodity data from ABARES. Significant negative correlations at 95 %, 99 % and 99.9 % confidence intervals were found between %-Area in drought category and crop cultivation area; export volume/value; crop yield; and rural debt. Our findings indicate that early warning of drought can be categorised by concern – wherein dry antecedent conditions and dry forecasted conditions are of the highest concern. The developed proof-of-concept DEWS contributes to the growing body of proactive drought management research. In a drought vulnerable future, operationalising and communicating drought early warnings will be critical to reducing the harmful impacts of drought on communities, economies, and environments. [ABSTRACT FROM AUTHOR]

Highlights • DfD model is proposed to estimate drainage from soil moisture (SM) drydowns. • Soil hydraulic properties are encoded in the shape of SM recession scatter plot. • The model best operate in permeable soil and humid climate. • By using SM2RAIN and DfD jointly, rainfall is estimated from SM data only. • There is a good potential of applying DfD to satellite soil moisture data. Abstract The large heterogeneity in soil surface conditions makes it impracticable to obtain reliable estimates of soil hydraulic parameters for areas larger than few squared kilometers. However, identifying these parameters on a global scale is essential for many hydrological and climatic applications. In this study, a new approach named Drainage from Drydown (DfD) is proposed to estimate the coefficients of drainage using soil moisture observations. DfD firstly selects multiple drydown events when surface runoff and evapotranspiration rates are negligible compared to the drainage rate. Secondly, by inverting the soil water balance equation, the drainage coefficients are obtained. Synthetic experiments are carried out in order to tune the overall procedure. DfD is then tested with in situ observations at 8 different sites worldwide characterized by different climates and soil types. The reliability of the DfD is evaluated by using the DfD drainage coefficients in a physically based soil water balance model (SWB) for simulating soil moisture and a rainfall estimation model (SM2RAIN). The results indicate that the climate and the soil conditions exert an important role in the occurrence and magnitude of drainage rate. DfD is found capable of correctly identify periods in which drainage rate is the dominant process. Drainage coefficients obtained from DfD are consistent with the expected soil hydraulic properties based on the soil texture and land cover at each site. By using DfD drainage coefficients to estimate rainfall and soil moisture via SM2RAIN and SWB, promising results are obtained with median correlation of 0.83 and 0.91 between estimated and in situ data. However, in sites characterized by high rate of evapotranspiration (>700 mm/year) and low permeable soil (e.g., clay) the DfD performance is reduced. Overall, DfD demonstrates the ability to decouple drainage and evapotranspiration processes and to estimate the drainage coefficients from in situ observations. [ABSTRACT FROM AUTHOR]

Pines in semi-arid mountain environments manage to survive and thrive despite the limited soil water, due to shallow soil depths, and overall water scarcity. This study aims to develop a method for computing soil evaporation, bedrock water uptake and transpiration from a natural, open forest, based on sap flow (Heat Ratio Method), soil moisture and meteorological observations. The water balance of individual trees was conceptualized with a geometric approach, using canopy projected areas and Voronoi (Thiesen) polygons. The canopy approach assumes that the tree’s root area extent is equal to its canopy projected area, while the Voronoi approach assumes that the tree roots exploit the open area that is closer to the tree than to any other tree. The methodology was applied in an open Pinus brutia forest (68% canopy cover) in Cyprus, characterized by steep slopes and fractured bedrock, during two hydrologically contrasting years (2015 wet, 2016 dry). Sap flow sensors, soil moisture sensors, throughfall and stemflow gauges were installed on and around eight trees. Rainfall was 507 mm in 2015 and 359 mm in 2016. According to the canopy approach, the sum of tree transpiration and soil evaporation exceeded the throughfall in both years, which implies that the trees’ bedrock water uptake exceeds the surface runoff and drainage losses. This indicated that trees extend their roots beyond the canopy-projected areas and the use of the Voronoi polygons captures this effect. According to the stand scale water balance, average throughfall during the two years was 81% of the rainfall. Transpiration was 61% of the rainfall in 2015, but only 32% in 2016. On the contrary, the soil evaporation fraction increased from 26% in 2015 to 35% in the dry year of 2016. The contribution of bedrock water to tree transpiration was 77% of rainfall in 2015 and 66% in 2016. During the summer months, trees relied 100% on the uptake of water from the fractured bedrock to cover their transpiration needs. Average monthly transpiration areas ranged between 0.1 mm d −1 in October 2016 and 1.7 mm d −1 in April 2015. This study shows that bedrock uptake could be an essential water balance component of semi-arid, mountainous pine forests and should be accounted for in hydrologic models. [ABSTRACT FROM AUTHOR]

Summary: Understanding all components of the water balance, especially temporal rainfall patterns, is essential to optimize water use in rain-fed agriculture area. The effect of temporal rainfall patterns on water balance, evapotranspiration (ET), and crop growth was evaluated by considering root water extraction of plants in a rain-fed maize field. Soil water contents at depths of 15, 30, 60, and 90cm were measured daily in 2-year growth seasons. A soil water balance approach was applied to estimate changes in daily soil water storage. For the detailed water partitioning of the water balance and root water extraction, the soil–water-atmosphere-plant (SWAP) model with water and crop modules was applied. Results suggested that the main depths of root water uptake occurred in the top 60cm soil layer. Crop transpiration (T) can reach a level above 40% of the total water consumption during all growth stages, and its reduction was mainly due to the dry condition of soil. The crop yield in 2010 was 1125kgha−1 higher than that in 2011, although the rainfall amount in that year was 132mm less than the rainfall amount in 2011. The water use efficiency (WUE) was also higher in 2010. Therefore, the influence of temporal rainfall patterns was clearly more important than rainfall amounts (water partitioning into evaporation (E), T, and soil water content). Growing season T/ET can be a potential parameter for maize productivity. The field can be irrigated at pivotal growth stages under dry conditions to obtain the optimal effect in improving WUE and increasing grain yield. The SWAP model was a useful tool to analyze water partitioning in the freeze–thaw zone. [Copyright &y& Elsevier]

Summary: In this paper we extend the usefulness of the TOPKAPI model by adding a Green-Ampt infiltration module and make the model and source code freely available on the internet as PyTOPKAPI. Then, we investigate the sensitivity of the PyTOPKAPI hydrological model to systematic bias in the variables rainfall and evapotranspiration, as well as the physically based soil properties that describe the model behaviour. The model sensitivity is assessed in terms of relative changes in the Soil Saturation Index (SSI), which is defined as the percentage of soil pore space filled by water. The volumetric soil moisture content, can be calculated from SSI using location dependent soil properties, if required. The model sensitivity is calculated at 7200 sites in South Africa, for a 2.5 year simulation period with a time-step of three hours. This large spatial extent gives results for a wide array of climates and land properties. Overall, the sensitivity of the model turns out to be a closely linear function of, and the same order of magnitude as (or less than), the forcing/parameter bias. This indicates that the model is robust to errors in forcing/parameters. The results also show that the best estimates of soil water can be obtained by improving estimates of the storage parameters and rainfall forcing. However, the storage parameters must be obtained from static soil property data-sets and we show that there is value in making improvements to the rainfall forcing (in this case TRMM 3B42RT) for places where it is biased relative to observed rainfall. This work is particularly relevant for model application in ungauged basins, where the quality of forcing variables and physical parameters cannot be calibrated. [Copyright &y& Elsevier]

Summary: We test the ability of three box models () to describe soil moisture dynamics in a regularly monitored experimental site in northwestern Italy. The models include increasingly complex representations of leakage and evapotranspiration processes. We force the models with the local rainfall, and we determine model parameters with a least-square minimization procedure. We study separately summer and annual dynamics. When we use the models to reproduce annual dynamics, we include a simple representation of the annual cycle of evapotranspiration. We test the models both in simulation mode, estimating their parameters from the same data used to verify them, and in forecast mode, determining the model parameters from one period, and using them to forecast soil water dynamics in a different period. The results indicate that simple box models can estimate soil water dynamics at midlatitudes, using rainfall as the only meteorological driver. The models displaying the best performances include the representation of leakage and evapotranspiration as nonlinear functions of soil water content. [ABSTRACT FROM AUTHOR]

Summary: New hydro-pedotransfer functions (HPTF) for flat grasslands are presented to estimate both annual capillary rise from the groundwater into the root zone and actual evapotranspiration on a regional scale. Based on easily available site information, soil water components such as percolation rate and therefore groundwater recharge can also be evaluated. This information may be obtained without detailed knowledge of soil hydraulic properties and daily weather data. Rather, the only data needed is soil texture class, groundwater depth, summer rainfall and potential evapotranspiration (ET 0) according to the FAO guideline. The basic idea is to evaluate the increase of actual evapotranspiration (=gain, G) caused by capillary rise from groundwater compared to identical site conditions, but without groundwater influence. This gain (G) represents an effective parameter to express both the soil and climate dependent effective capillary rise for a given grassland site. To develop hydro-pedotransfer functions expressing gain, we first used the numerical simulation program SWAP in order to calculate water balances for a broad spectrum of soils, groundwater depths, and climate conditions. Secondly we analyzed this data statistically in order to obtain simple equations for predicting G without using a numerical model. The new hydro-pedotransfer functions were developed and tested for different climate regions in Germany. [ABSTRACT FROM AUTHOR]

Summary: Simple equations relating recharge estimates from previous soil water-budget studies in Hawaii, USA, to mean annual rainfall, soil infiltration, and infiltration minus potential evapotranspiration (PE) were developed. Tests indicate that the equations can be used to estimate groundwater recharge on other tropical islands, but each equation has a different degree of accuracy. In general, the equations will have smaller relative errors in regions having wet climates. The rainfall equation is the least accurate; its use is limited to applications that do not require the highest accuracy. The infiltration and infiltration-minus-PE equations are more accurate and may be useful for regional recharge estimates in areas having mostly high rainfall or a mix of high to moderate rainfall. Transferability of the equations is limited to areas where the predominant climate and soil characteristics are generally similar to those in Hawaii. The equations also may not be accurate enough for estimates where high spatial or temporal detail or accuracy is required. Despite these limitations, the equations can provide a simple and quick generalized estimate of regional recharge for many tropical islands. Because of their simplicity, the equations may be particularly useful for providing a quick and independent estimate of recharge to compare with estimates determined by other methods. [Copyright &y& Elsevier]

Summary: The African Monsoon Multidisciplinary Analysis (AMMA) is an international and interdisciplinary experiment designed to investigate the interactions between atmospheric, oceanic and terrestrial systems and their joint controls on tropical monsoon dynamics in West Africa. This special issue reports results from a group of AMMA studies regrouped in the component “Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique” (CATCH). AMMA-CATCH studies focus on measuring and understanding land surface properties and processes in West Africa, the role of terrestrial systems in altering boundary layer dynamics, and thus the potential that surface hydrology and biology, and human land use practices, may directly or indirectly affect monsoon dynamics and rainfall in the region. AMMA-CATCH studies focus on three intensively instrumented mesoscale sites in Mali, Niger and Benin that sample across the 100–1300mm/annum rainfall gradient of the Sahel, Sudan and North-Guinean bioclimatic zones. Studies report on: (i) surface–boundary layer interactions that may influence atmospheric convergence and convective processes and thus rainfall type, timing and amount; (ii) vegetation dynamics at seasonal to decadal time-scales that may respond to, and alter, atmospheric processes; (iii) surface–atmosphere fluxes of heat, water and carbon dioxide that directly influence the atmosphere; (iv) soil moisture variability in space and time that provide the proximate control on vegetation activity, evapotranspiration and energy balance; and (v) local and mesoscale modeling of hydrology and land surface–atmosphere exchanges to assess their role in the hydrological, atmospheric and rainfall dynamics of West Africa. The AMMA-CATCH research reported in this issue will be extended in future years as measurements and analysis continue and are concluded within the context of both CATCH and the wider AMMA study. This body of research will contribute to an improved understanding of the functioning of the coupled West African system, and enhance our ability to model and predict rainfall, vegetation and biogeochemical dynamics across time-scales (day, year, decade, and century), and in response to changing climate and land use. Such information is vital for policy makers and managers in planning for future economic development, sustainability and livelihoods of the growing populations of the region. [Copyright &y& Elsevier]

Abstract: Estimation of recharge in a variety of climatic conditions is possible using a daily soil moisture balance based on a single soil store. Both transpiration from crops and evaporation from bare soil are included in the conceptual and computational models. The actual evapotranspiration is less than the potential value when the soil is under stress; the stress factor is estimated in terms of the readily and total available water, parameters which depend on soil properties and the effective depth of the roots. Runoff is estimated as a function of the daily rainfall intensity and the current soil moisture deficit. A new concept, near surface soil storage, is introduced to account for continuing evapotranspiration on days following heavy rainfall even though a large soil moisture deficit exists. Algorithms for the computational model are provided. The data required for the soil moisture balance calculations are widely available or they can be deduced from published data. This methodology for recharge estimation using a soil moisture balance is applied to two contrasting case studies. The first case study refers to a rainfed crop in semi-arid northeast Nigeria; recharge occurs during the period of main crop growth. For the second case study in England, a location is selected where the long-term average rainfall and potential evapotranspiration are of similar magnitudes. For each case study, detailed information is presented about the selection of soil, crop and other parameters. The plausibility of the model outputs is examined using a variety of independent information and data. Uncertainties and variations in parameter values are explored using sensitivity analyses. These two case studies indicate that the improved single-store soil moisture balance model is a reliable approach for potential recharge estimation in a wide variety of situations. [Copyright &y& Elsevier]

• The FAO-56 method was conceptually combined with the complementary principle. • The reference evapotranspiration was deflated by temperature correction. • The water stress coefficient was estimated by a generalized complementary principle. • A crop coefficient curve was developed for a local crop field by inverting the hybrid approach. In this study, we proposed a hybrid approach combining the standard FAO-56 method with the complementary principle of evapotranspiration (ET) to predict actual ET (ET a) on a rainfed crop field. A generalized complementary relationship (GCR) was employed to quantify the water stress coefficient (K s) for the FAO-56 method with no use of soil moisture data. Then, the K s values were multiplied to the crop ET (ET c) estimated with the corrected air temperatures for the assumption of adequate land-surface moisture. The proposed hybrid method applied to a rotational maize-soybean field where an eddy-covariance flux tower was installed. Results showed that the reference ET (ET o) estimated by the corrected temperatures was within a range of 89–95% of that from non-corrected ones, implying that ET o could be inflated when using the mean air temperatures measured under sub-humid conditions. The K s values estimated by GCR showed consistent patterns with temporal rainfall variation on the field. The multiplication of the K s from GCR and ET c showed higher performance in ET a prediction than when the GCR was solely applied. By inverting the hybrid approach, a local crop coefficient curve for the rainfed maize field was developed, and led to further improvement in ET a prediction. This study suggests that combination of the complementary principle and the FAO-standard method, which are seemingly in separate paradigms, may improve ET a prediction on crop fields. [ABSTRACT FROM AUTHOR]