The impact of convection-permitting model rainfall on the dryland water balance

Climate change impacts on water security in global drylands

Floodplain forests provide unique ecological structure and function, which are often degraded or lost when watershed hydrology is modified. Restoration of damaged ecosystems requires an understanding of surface water, groundwater, and vadose (unsaturated) zone hydrology in the floodplain. Soil moisture and porewater salinity are of particular importance for seed germination and seedling survival in systems affected by saltwater intrusion but are difficult to monitor and often overlooked. This study contributes to the understanding of floodplain hydrology in one of the last bald cypress [Taxodium distichum (L.) Rich.] floodplain swamps in southeast Florida. We investigated soil moisture and porewater salinity dynamics in the floodplain of the Loxahatchee River, where reduced freshwater flow has led to saltwater intrusion and a transition to salt-tolerant, mangrove-dominated communities. Twenty-four dielectric probes measuring soil moisture and porewater salinity every 30 min were installed along two transects-one in an upstream, freshwater location and one in a downstream tidal area. Complemented by surface water, groundwater, and meteorological data, these unique 4-yr datasets quantified the spatial variability and temporal dynamics of vadose zone hydrology. Results showed that soil moisture can be closely predicted based on river stage and topographic elevation (overall Nash-Sutcliffe coefficient of efficiency = 0.83). Porewater salinity rarely exceeded tolerance thresholds (0.3125 S m(-1)) for bald cypress upstream but did so in some downstream areas. This provided an explanation for observed vegetation changes that both surface water and groundwater salinity failed to explain. The results offer a methodological and analytical framework for floodplain monitoring in locations where restoration success depends on vadose zone hydrology and provide relationships for evaluating proposed restoration and management scenarios for the Loxahatchee River.

Soil temperature and moisture are the key variables that control the overall effect of climate and topography on soil and vegetation in alpine regions. However, there has been little investigation of the potential soil temperature and moisture feedbacks on climate changes in different alpine ecosystems and their impact on vegetation change. Soil temperature and moisture at five depths were measured continuously at 10-min intervals in three typical ecosystems (Kobresia meadow (KMd), Achnatherum splendens steppe (ASSt), and Potentilla fruticosa shrub (PFSh)) of the Qinghai Lake watershed on the northeast Qinghai-Tibet Plateau, China. The findings of this study revealed that the KMd and PFSh sites had relatively low soil temperature and high soil moisture, whereas the ASSt site had relatively warm soil temperature and low soil moisture. The soil and vegetation characteristics had important effects on the infiltration process and soil moisture regime; about 47%, 87%, and 34% of the rainfall (minus interception) permeated to the soil in the KMd, PFSh, and ASSt sites, respectively. In the context of the warming climate, changes to soil moisture and temperature are likely to be the key reasons of the alpine meadow deterioration and the alpine shrub expansion in the alpine regions.

Understanding the relationship between streamflow and climate input is important to inform how streamflow characteristics could change under climate change. The first part of this study assessed the relationship between annual streamflow and climate characteristics using rainfall, potential evapotranspiration (PET) and streamflow data from 133 catchments across the Murray–Darling Basin (MDB). The second part assessed the response of key streamflow metrics (mean annual runoff, high-flow days, low-flow days and minimum three-year flow) to changes in rainfall characteristics and PET using a weather generator and five hydrological models. The results indicate that annual streamflow is strongly correlated to many rainfall characteristics. However, these rainfall characteristics are also strongly correlated to annual rainfall, and therefore annual rainfall is generally a good predictor of annual streamflow. Rainfall characteristics that have a secondary influence on annual streamflow include effective rainfall, which is defined as the cumulative positive differences between daily or monthly rainfall and PET, rainfall seasonality, multi-day rainfall totals and multi-year rainfall lows. The change in future mean annual streamflow is driven primarily by the change in mean annual rainfall and PET, followed by some of the rainfall characteristics above. In addition to mean annual rainfall, high flows are also strongly influenced by multi-day rainfall totals, while multi-year hydrological droughts are also influenced by multi-year rainfall lows and annual rainfall variability. These results are useful to identify the key climate characteristics in assessing the impacts of future climate change on water availability, and potentially for developing next-generation hydrological models that can deal with non-stationarity and better predict streamflow under a changing climate.

] Dai [2011] (henceforth D11) reported that the PalmerDrought Severity Index (PDSI) is superior to other statisti-cally based drought indices including the StandardizedPrecipitation Index (SPI) and the Standardized PrecipitationEvapotranspiration Index (SPEI). D11 argued that given thephysical character of the PDSI water balance model, theindex provides robust estimates of drought severity becauseit takes the preceding conditions into account, in contrast toother drought indices that are based purely on past statisticsof particular climate variable(s). However, D11 has over-estimated the ability of the PDSI to realistically simulate thedistributed soil water balance at large spatial scales, andignored the inherent complexity and multiscalar character ofdrought phenomena, which are related to more than themoisture conditions of the soil. In this comment we discussthe complex characteristics of droughts and the limitationsof the PDSI to quantify drought conditions in a variety ofhydrological systems. We describe the advantages of statis-tically based drought indices including the SPI and the SPEI.ThefactthattheSPIandtheSPEIarenot(anddonotintendtobe) physically based indices is more liberating than con-straining, especially when the physical basis of PDSI can beseriously questioned.[

Nowadays heat waves are a growing issue, causing detrimental effects on society, people’s health and environment in several parts of the world. Slow drivers such as spring soil moisture and sea surface temperature are known to impact the probability of occurrence of heatwaves in many areas of the globe. However, their influence remains still little understood and studied. Even fewer has been said on the cross effect and relative impact of both factors. Our work aims at analysing and comparing the effects of spring soil moisture deficit in Europe and sea surface temperature decadal variability in the North Atlantic (AMV) on the occurrence of typical and more extreme European heat waves. To do that, we use the outputs from three climate models, namely IPSL-CM6A-LR, EC-Earth3 and CNRM-CM6-1, in which North Atlantic sea surface temperatures are nudged to the observed AMV anomalies.At a methodological level, previous studies mainly focused on typical heat waves. Our work goes beyond that and proposes a new methodology to study events with larger return times. By introducing return time maps we can study rare heatwaves with return time from 10 to 50 years. We find that the temperature and duration of typical and extreme heatwaves are influenced by the AMV and soil moisture. In general, the changes induced by typical AMV or soil moisture anomalies are of comparable amplitude. In many areas of Europe, the influence of AMV and soil moisture over duration or temperature of extreme heatwaves increases when the return time is longer and is statistically significant even for return times of 50 years. In general, the three models give consistent results. With positive AMV phase or low soil moisture, the temperature and duration of extreme heatwaves are changed according to regional patterns. As might be expected, positive AMV phase or low soil moisture often induce hotter and longer typical and extreme heatwaves. However, counter-intuitively, they also induce cooler and shorter heatwaves over part of Northern-Eastern Europe. For more extreme events, the impact of the AMV and soil moisture increases, according to rather similar regional patterns. However, the regions with decreased temperature or duration impact extend in size.In this work, we have improved the study of extreme heat waves and better understood their slow drivers. Studying those drivers is important to enhance heat wave predictability. To move further in this direction, we need to improve the statistics of the events. In this context, developing and using new tools such as rare event simulations might be the right path to follow.

Spatio-temporal variations in global surface soil moisture based on multiple datasets: Intercomparison and climate drivers

Global Water Balance According to the Penman Approach*

African society is particularly vulnerable to climate change. The representation of convection in climate models has so far restricted our ability to accurately simulate African weather extremes, limiting climate change predictions. Here we show results from climate change experiments with a convection-permitting (4.5 km grid-spacing) model, for the first time over an Africa-wide domain (CP4A). The model realistically captures hourly rainfall characteristics, unlike coarser resolution models. CP4A shows greater future increases in extreme 3-hourly precipitation compared to a convection-parameterised 25 km model (R25). CP4A also shows future increases in dry spell length during the wet season over western and central Africa, weaker or not apparent in R25. These differences relate to the more realistic representation of convection in CP4A, and its response to increasing atmospheric moisture and stability. We conclude that, with the more accurate representation of convection, projected changes in both wet and dry extremes over Africa may be more severe.

Evapotranspiration is an important process in the water balance. It accounts for water transported from the surface of the Earth to the atmosphere. For practical applications, the estimation of evapotranspiration is limited by the potential evapotranspiration (PET), which is the maximum evapotranspiration that occurs when the availability of water on the surface is unlimited. PET can be estimated based on different climate variables. When assessing climate change projections, different climate models often project different change directions for such variables. Furthermore, the reliability of the climate model projections varies for each variable. Therefore, the uncertainty associated with the estimation of PET can be large. This study assesses this uncertainty by employing ten methods commonly used to estimate PET for ten different locations across Europe, capturing different climate and physical conditions. An ensemble of ten Euro-CORDEX climate models is used to assess projected PET changes through the century under the RCP 8.5 scenario. Different climate model bias correction methods are employed to reduce the biases in the climate model outputs when compared to the reference climate. A pseudo-reality experiment is set where each climate model acts as reference to train the correction methods, which are applied to the climate models that remain in the ensemble. The uncertainty of the projected PET is compared to the reference-climate-PET using evaluation metrics. Results are relevant for decision and policy makers and professionals developing impact studies.

Soil structure is nearly as important as soil texture in determining the soil hydraulic properties at the core scale. Soil structure was also shown to significantly affect runoff and drainage at ecosystem scale (Fatichi et al., 2020; Bonetti et al., 2021). However, its effect on vadose zone hydrology at 100 km scale — at which climate and land surface models are often run — remains unclear. Seminal works (Fatichi et al., 2020; Bonetti et al., 2021) found a small effect of soil structure at these large scales, but this has been linked to the nature of the subgrid parametrization of precipitation (or of soil hydraulic conductivity) in the employed models. Here, we evaluate the effect of soil structure on vadose zone hydrology in the ORCHIDEE land surface model, which models infiltration using a unique subgrid parametrization of soil hydraulic conductivity (Vereecken et al., 2019). In ORCHIDEE, we find a larger effect of soil structure on the water cycle than reported for OLAM (Fatichi et al., 2020). We link this to the subgrid variability of hydraulic conductivity in ORCHIDEE, which ensures that the structural modifications of soil hydraulic properties are activated at all rainfall rates. Finally, we discuss the perspectives for parametrizing the structural modifications of soil hydraulic properties at large scales using soil moisture observations.Bonetti, S., Wei, Z., & Or, D. (2021). A framework for quantifying hydrologic effects of soil structure across scales. Communications Earth & Environment, 2 (1), 1–10. https://doi.org/10.1038/s43247-021-00180-0Fatichi, S., Or, D., Walko, R., Vereecken, H., Young, M. H., Ghezzehei, T. A., Hengl, T., Kollet, S., Agam, N., & Avissar, R. (2020). Soil structure is an important omission in Earth System Models. Nature Communications, 11 (1), 522. https://doi.org/10.1038/s41467-020-14411-zVereecken, H., Weihermüller, L., Assouline, S., Šimůnek, J., Verhoef, A., Herbst, M., Archer, N., Mohanty, B., Montzka, C., Vanderborght, J., Balsamo, G., Bechtold, M., Boone, A., Chadburn, S., Cuntz, M., Decharme, B., Ducharne, A., Ek, M., Garrigues, S., … Xue, Y. (2019). Infiltration from the Pedon to Global Grid Scales: An Overview and Outlook for Land Surface Modeling. Vadose Zone Journal, 18 (1), 180191. https://doi.org/10.2136/vzj2018.10.019

There is antidotal evidence that many farmers in Puerto Rico do not employ scientific methods for scheduling irrigation for their crops. Instead, the pump is turned on for an arbitrary amount of time without knowing whether the amount of water applied is too much or too little. Over application of water can lead to the waste of water, energy, chemicals and money, and also may lead to the contamination of ground and surface waters. Under-application of irrigation can lead to reduced crop yields and a loss of revenue to the grower. There are various approaches for scheduling irrigation. One approach is to supplement rainfall with enough irrigation so that the cumulative rainfall and irrigation, over a specific period of time (e.g., one day, one week, one season), matches the estimated potential evapotranspiration, which is equivalent to the crop water requirement. Potential evapotranspiration (ETc) can be estimated by the product of a crop coefficient (Kc) and the reference evapotranspiration (ETo). Traditionally, potential evapotranspiration is derived from pan evaporation data or meteorological data from weather stations. Another approach involves monitoring the soil moisture and applying irrigation sufficient to maintain the soil moisture content within a predetermined range. In this paper we present an approach based on applying irrigation to the crop to meet the crop water requirements (i.e., potential evapotranspiration), but instead of using pan evaporation or meteorological data, we use a remote sensing technique. The advantage of the method is tha t reference evapotranspiration can be estimated at a 1 km resolution for the entire island each day. If the relatively simple approach presented in this paper is used it can potentially lead to increased efficiency of water and energy use, and help to reduce crop water stress and losses in crop yields. Potential crop evapotranspiration is estimated by using the simple relation

Grasshopper eggs overwinter in soil for almost half a year. Changes in soil temperature and moisture have a substantial effect on grasshopper eggs, especially temperature and moisture extremes. However, the combinatorial effect of temperature and moisture on the development and survival of grasshopper eggs has not been well studied. Here, we examined the effects of different soil moistures (2, 5, 8, 11, 14% water content) at 26°C and combinations of extreme soil moisture and soil temperature on the egg development and survival of three dominant species of grasshopper (Dasyhippus barbipes, Oedaleus asiaticus, and Chorthippus fallax) in Inner Mongolian grasslands. Our data indicated that the egg water content of the three grasshopper species was positively correlated with soil moisture but negatively correlated with hatching time. The relationship between hatching rate and soil moisture was unimodal. Averaged across 2 and 11% soil moisture, a soil temperature of 35oCsignificantly advanced the egg hatching time of D. barbipes, O. asiaticus, and C. fallax by 5.63, 4.75, and 2.63 days and reduced the egg hatching rate of D. barbipes by 18%. Averaged across 26 and 35°C, 2% soil moisture significantly delayed the egg hatching time of D. barbipes, O. asiaticus, and C. fallax by 0.69, 11.01, and 0.31 days, respectively, and decreased the egg hatching rate of D. barbipes by 10%. The hatching time was prolonged as drought exposure duration increased, and the egg hatching rate was negatively correlated with drought exposure duration, except for O. asiaticus. Overall, the combination of high soil temperature and low soil moisture had a significantly negative effect on egg development, survival, and egg hatching. Generally, the response of grasshopper eggs to soil temperature and moisture provides important information on the population dynamics of grasshoppers and their ability to respond to future climate change.

Seedlings of the snap bean (Phaselous vulgaris L.), cv. Kentucky Wonder, were inoculated with ≈0, 240, 2400, or 24,000 root knot [Meloidogyne hapla (Chitwood)] nematodes per plant and grown in a sandy soil in the greenhouse at a soil water potential of either −0.025 (high soil moisture) or −0.075 (low soil moisture) MPa. Leaf xylem potential, transpiration, root hydraulic conductivity, and nematode populations in roots, as well as growth and yield data, were collected about 8 weeks after inoculation. Transpiration was reduced by decreasing soil moisture—maximum transpiration occurred about midday at high soil moisture and in the early morning at low soil moisture. Transpiration decreased late in the day with increasing nematode populations at high, but not low, soil moisture. Leaf xylem potential was reduced by low soil moisture and nematodes but interactive effects were not significant. Root conductivity was lower in plants exposed to low soil moisture than in plants maintained at high soil moisture. However, nematodes reduced conductivity in only one of two experiments, and interactive effects were not significant in either experiment. Root and shoot dry weight and leaf area were decreased in response to low soil moisture. Nematodes reduced shoot dry weight and leaf area, but not root dry weight, in one of two experiments and there were no significant interactive effects in either experiment. Total yields of beans were reduced at low soil moisture and in response to nematode inoculum. A significant interactive effect on early bean yield was also evident; nematodes lowered early yields more at high soil moisture than at low soil moisture. These data indicate that although soil moisture and M. hapla populations individually influenced water relations, growth, and yield of bean, the interactive effects were generally not significant. When an interaction could be demonstrated, it was due to a decreased effect of nematodes at low soil moisture.

Abstract. Potential evapotranspiration (PET) is the water that would be lost by plants through evaporation and transpiration if water was not limited in the soil, and it is commonly used in conceptual hydrological modelling in the calculation of runoff production and hence river discharge. Future changes of PET are likely to be as important as changes in precipitation patterns in determining changes in river flows. However PET is not calculated routinely by climate models so it must be derived independently when the impact of climate change on river flow is to be assessed. This paper compares PET estimates from 12 equations of different complexity, driven by the Hadley Centre's HadRM3-Q0 model outputs representative of 1961–1990, with MORECS PET, a product used as reference PET in Great Britain. The results show that the FAO56 version of the Penman–Monteith equations reproduces best the spatial and seasonal variability of MORECS PET across GB when driven by HadRM3-Q0 estimates of relative humidity, total cloud, wind speed and linearly bias-corrected mean surface temperature. This suggests that potential biases in HadRM3-Q0 climate do not result in significant biases when the physically based FAO56 equations are used. Percentage changes in PET between the 1961–1990 and 2041–2070 time slices were also calculated for each of the 12 PET equations from HadRM3-Q0. Results show a large variation in the magnitude (and sometimes direction) of changes estimated from different PET equations, with Turc, Jensen–Haise and calibrated Blaney–Criddle methods systematically projecting the largest increases across GB for all months and Priestley–Taylor, Makkink, and Thornthwaite showing the smallest changes. We recommend the use of the FAO56 equation as, when driven by HadRM3-Q0 climate data, this best reproduces the reference MORECS PET across Great Britain for the reference period of 1961–1990. Further, the future changes of PET estimated by FAO56 are within the range of uncertainty defined by the ensemble of 12 PET equations. The changes show a clear northwest–southeast gradient of PET increase with largest (smallest) changes in the northwest in January (July and October) respectively. However, the range in magnitude of PET changes due to the choice of PET method shown in this study for Great Britain suggests that PET uncertainty is a challenge facing the assessment of climate change impact on hydrology mostly ignored up to now.