Soil Water Balance Model Research Articles

Crop Yield and Water Use Efficiency as Affected by Different Soil-Based Management Methods for Variable-Rate Irrigation in a Semi-Humid Climate

Abstract. To improve the management of variable-rate irrigation (VRI) systems in semi-humid climates, three different soil-based irrigation management methods were evaluated on their potential for reducing irrigation water use and maximizing crop yield and water use efficiency (WUE) during the 2016 and 2017 growing seasons of summer maize in the North China Plain. The three irrigation management methods evaluated were soil water balance modeling (SWB), measured soil water content (SWC), and a combination of SWB and the rain forecast for the next three days (RF). The experiments were implemented on four management zones delineated by available soil water holding capacity of a center-pivot VRI system. A similar irrigation trigger point (70% of field capacity) was used for the three irrigation management methods in the four management zones. In the two seasons, the total water application in the SWC treatments varied in a larger range among the management zones, and the irrigation water applied was 22% and 21% less than in the SWB and RF treatments, respectively. Similar yields were obtained among the irrigation management methods in both seasons. The maximum WUE was always observed with the SWC treatments for the four management zones in the 2017 season. The WUE with the SWC treatments was 36% and 23% higher than with the SWB and RF treatments, respectively. Considering the amount of irrigation water applied, yield, and WUE, our results demonstrated that the SWC method was more suitable for VRI management than the SWB and RF methods in this semi-humid climate. Keywords: Center pivot, Soil water balance, Soil water content, Rain forecast, Summer maize, Yield.

A Coupled Soil Water Balance Model for Simulating Depression‐Focused Groundwater Recharge

Core Ideas Ephemeral ponds in depressions are the foci of groundwater recharge in the Canadian Prairies. Freeze–thaw processes influence snowmelt runoff and depression‐focused recharge. A new water balance model was developed to represent these processes. The water balance model successfully simulated the observed soil processes. This model will provide a tool to estimate recharge in the prairie landscape. In arid and semiarid environments, focused infiltration of rain and snowmelt water under topographic depressions is an important mechanism of groundwater recharge. Quantifying the aggregated recharge from numerous small depressions is a major challenge in water resource management. Building on field‐based investigations into the surface water–groundwater interaction of individual depressions and their catchments (i.e., uplands) in the Canadian Prairies, we have developed a simple water balance model to simulate groundwater recharge considering the hydrological coupling of a depression–upland system. The model is based on the Versatile Soil Moisture Budget (VSMB), which has been widely used in the Canadian Prairies to simulate soil moisture conditions. We evaluated the new model, VSMB Depression‐Upland System (VSMB‐DUS), using field data consisting of an artificial flooding experiment and long‐term monitoring of a depression in Alberta, Canada. The model captured surface water level, soil moisture, and groundwater responses to the artificial flooding with reasonable accuracy and represented the interannual variability of recharge fluxes during a 5‐yr period (2007–2011), including dry and wet years. Simulated annual recharge varied between 12 and 45 mm, and annual precipitation varied between 453 and 597 mm during the 5‐yr period. The VSMB‐DUS tends to over‐ or underestimate snowmelt runoff in individual years; however, simulated recharge was only slightly affected by the errors in snowmelt runoff estimation. Due to its computational efficiency and robust algorithms, the VSMB‐DUS will provide a useful tool for estimating aggregated recharge in a large‐scale model grid cell containing hundreds of depression‐upland systems.

Complementary Irrigation in a Maize Silage Double Crop using the BAHICU Software: A Case Study in Northern Buenos Aires, Argentina

Northern Buenos Aires (Argentina) is a rain fed agricultural region. Complementary irrigation, which is mainly used in maize crop, requires the contemplation of strategies that minimize the soil solidification risk. The first alternative to mitigate the limited water quality is to perform an irrigation schedule by using the water balance methodology. The BAHICU software, developed in the study region, is a soil water balance model for agricultural systems under irrigation. The objective of the present study was to evaluate the forage production of irrigated and rain fed double crop of silage maize, using the BAHICU software as a tool to make a more efficient water use and to attenuate the adverse effect of the sodium present in the irrigation water. A field experiment was conducted on a clay soil with a sequence of two maizes during the 2015-2016 growing season: short season maize (maize 1) and late sown maize (maize 2). There were two preceding winter crops: ryegrass and oat. Plant height, dry matter (DM) percentage and DM yield were measured. Crop evapotranspiration (ETc) of irrigated and rain fed treatments was obtained from the BAHICU software. Irrigation was applied using a sprinkler system. Irrigation influenced only the yield of maize 2. Water use efficiency (WUE) did not vary with irrigation incorporation. Maize 2 presented higher forage production and WUE than maize 1. An R2 value of 0.82 was found after relating DM yield with maize ETc. The preceding winter crops only influenced the yield of the maize 1. The DM yield was linked to plant height. The irrigated maize 2 was the only treatment that presented an optimal DM percentage for silage conservation. Using the BAHICU software allowed comparing the WUE of the maizes analyzed. Irrigation influenced crop yield but not WUE.

Water requirements of short rotation poplar coppice: Experimental and modelling analyses across Europe

Poplars are among the most widely used short rotation woody coppice (SRWC) species but due to their assumed high water use, concerns have been raised with respect to large-scale exploitation and potentially detrimental effects on water resources. Here we present a quantitative analysis of the water requirements of poplar SRWC using experimental data and a soil water balance modelling approach at three different sites across Europe. We used (i) eddy covariance (EC) measurements (2004–2006) at an irrigated SRWC grown on a previous rice paddy in northern Italy, (ii) Bowen ratio and energy balance (BREB) measurements (2008–2015) and EC (2011–2015) at a SRWC in rain-fed uplands in the Czech Republic, and (iii) EC measurements (2010–2013) at a SRWC on a previous agricultural land with a shallow water table in Belgium. Without any calibration against water balance component measurements, simulations by the newly developed soil water balance model R-4ET were compared with evapotranspiration (ET) measurements by EC and BREB with a resulting mean root mean square error (RMSE) of 0.75 mm day−1. In general, there was better agreement between EC and the model (RMSE = 0.66 mm day−1) when EC data were adjusted for lack of energy balance closure. A comparison of the simulated and measured soil water content yielded a mean RMSE of 0.03 m3 m−3. The mean annual crop coefficient, i.e. the ratio between actual and reference ET, was 0.82 (ranging from 0.65 to 0.95) while the monthly maxima reached 1.16. These values indicated that ET of poplar SRWC was significantly lower than ET of a well-watered grass cover at the annual time scale, but exceeded ET of the reference cover at shorter time scales during the growing season. We show that the model R-4ET is a simple, yet reliable tool for the assessment of water requirements of existing or planned SRWC. For very simple assessments on an annual basis, using a crop coefficient of 0.86 (adjusted to a sub-humid climate), representing an average value across the three sites in years with no evident drought stress, is supported by this analysis.

Land degradation affects shrub growth responses to precipitation in a semiarid rangeland of north‐eastern Patagonia (Argentina)

AbstractArid land degradation diminishes the proportion of precipitation conducted to infiltration and increases the proportion lost to run‐off and evaporation. Consequently, we expect that the effects of annual precipitation on shrub growth vary with land degradation as a result of changes in soil available water. Chuquiraga avellanedae is the dominant shrub and the main indicator of land degradation in semiarid rangelands of north‐eastern Patagonia. We chose two communities with a different degree of land degradation: an herbaceous steppe with shrubs (HSS) and a degraded shrub steppe (SS). Vegetative growth of C. avellanedae was determined nondestructively using a double‐sampling approach. Soil water content was estimated for the two communities using a soil water balance model. Linear regressions were used to evaluate the relationships between shrub growth and (i) annual precipitation and (ii) mean available water during the period of high vegetative growth in the soil layer that each plant community concentrates their roots. In SS, with elevated clay content, there were more roots of C. avellanedae in the upper layers of soil while in HSS, with coarse‐textured soil, C. avellanedae had more roots in deeper layers. Vegetative growth of C. avellanedae, both in HSS and SS communities, was positively related to annual precipitation but, for a given precipitation, C. avellanedae presented higher vegetative growth in HSS than in SS. We also found a positive relationship between vegetative growth and soil available water, and this relationship did not differ between communities. SS presented lower water availability because of lower infiltration rates. Our results showed that, irrespective of the degree of land degradation, plants respond directly to water content of the soil layers where most roots are present at a specific window of time.

On the synergy of SMAP, AMSR2 AND SENTINEL-1 for retrieving soil moisture

An algorithm for retrieving soil moisture content (SMC) from synergic use of both active and passive microwave acquisitions is presented. The algorithm takes advantage of the integration of microwave data from SMAP, Sentinel-1 and AMSR2 for overcoming the SMAP radar failure and obtaining a SMC product at enhanced resolution (0.1°×0.1°) and improved accuracy with respect to the original SMAP radiometric SMC product. A disaggregation technique based on the Smoothing filter based intensity modulation (SFIM) allows combining the radiometric and SAR data. Disaggregated microwave data are used as inputs of an Artificial Neural Networks (ANN) based algorithm, which is able to exploit the synergy between active and passive acquisitions. The algorithm is defined, trained and tested using the SMEX02 experimental dataset and data simulated by forward electromagnetic models based on the Radiative Transfer Theory. Then the algorithm is adapted to satellite data and tested using one year of SMAP, AMSR2 and Sentinel-1 co-located data on a flat agricultural area located in the Po Valley, in northern Italy. Spatially distributed SMC values at 0.1°× 0.1° resolution generated by the Soil Water Balance Model (SWBM) are considered as reference for this purpose. The synergy of SMAP, Sentinel-1 and AMSR2 allowed increasing the correlation between estimated and reference SMC from R≅0.68 of the SMAP based retrieval up to R≅0.86 of the combination SMAP+Sentinel–1+AMSR2. The corresponding Root Mean Square Error (RMSE) decreased from RMSE≅0.04m3/m3 to RMSE≅0.024m3/m3.

Effect of climatic and soil moisture conditions on mushroom productivity and related ecosystem services in Mediterranean pine stands facing climate change

Wild mushrooms contribute to a variety of ecosystem services. The expected warmer and drier conditions for the Mediterranean region as a consequence of climate change, are raising concerns about future mushroom productivity due to potential reduction of soil water availability for fungi. The aim of this study was to increase our understanding of the interaction between climate and soil moisture in relation to their impact on mushroom productivity in Mediterranean forests. Mushroom yield data were obtained from 28 permanent mushroom inventory plots intensively monitored in Maritime pine (Pinus pinaster Ait.) stands of northeastern Iberian Peninsula. Annual productivity of total, edible and marketed mushrooms was obtained from measurements conducted every week during the autumn fruiting season for years 2008–2015. Historical weather conditions were obtained through data interpolation from meteorological stations. Soil moisture data were obtained from continuous plot-level measurements. A process-based soil water balance model was used to predict soil moisture under two climate change scenarios, using the predictions of two different regional climate models. Mixed-effects models using either precipitation or soil moisture as predictors, in combination with other weather variables, were fitted to annual mushroom occurrence and yield data. Mushroom yield was primarily dependent on weather and soil moisture conditions during the same month, with the exception of precipitation, whose effects exhibited a one-month delay. High temperatures limited mushroom yield at the beginning of the fruiting season, but tended to enhance it towards the end. The analysis revealed no apparent negative effect of climate change on long-term mushroom productivity, but rather the opposite (i.e., predicted median productivity of marketed mushrooms for 2016–2100 was 23–93% higher compared to the current yield), mainly due to an elongation of the fruiting season arising from the combined effect of increased precipitation at the beginning of the season and warmer temperatures at the end.

Modeling Regional Soil Water Balance in Farmland of the Middle Reaches of Heihe River Basin

Quantifying components of soil water balance in farmland of the middle reaches of Heihe River Basin is essential for efficiently scheduling and allocating limited water resources for irrigation in this arid region. A soil water balance model based on empirical assumptions in the vadose zone of farmland was developed and simulation results were compared/validated with results by the numerical model HYDRUS-1D. Results showed a good coherence between the simulated results of the water balance models and the HYDRUS-1D model in soil water storage, evapotranspiration, deep percolation and groundwater recharge, which indicated that the water balance model was suitable for simulating soil water movement in the study area. Considering the spatial distribution of cropping patterns, groundwater depth and agricultural management, ArcGIS was applied for the pre-/post-processing of the water balance model to quantify the spatial distribution of components of soil water balance in the major cropland in middle reaches of Heihe River Basin. Then, distributions of components of soil water balance in the major cropland under different water-saving irrigation practices during the growing season were predicted and discussed. Simulation results demonstrated that evapotranspiration of the main crops would be more prominently influenced by irrigation quota under deep groundwater depth than that under shallow groundwater depth. Groundwater recharge would increase with the increase of irrigation quota and decrease with the increase of groundwater depth. In general, when groundwater depth reached 3 m, groundwater recharge from root zone was negligible for spring wheat. While when it reached 6 m, groundwater recharge was negligible for maize. Water-saving irrigation practices would help to reduce groundwater recharge with a slight decrease of crop water consumption.

Field capacity, a valid upper limit of crop available water?

“Field capacity” (FC) is an agronomic measure with prime application in irrigation management, allowing the determination of irrigation gift without excessive leaching. FC can be determined by performing or simulating an internal drainage experiment until percolation reaches a “negligible” value. Alternatively, a static value of pressure head is often used to estimate FC, commonly −3.3m, −1m or −0.6m. FC is also used in definitions regarding soil water availability to crops and has been adopted in soil water balance models to define the maximum water storage. Nevertheless, crop water uptake may occur at water contents higher than FC. This uptake may represent a significant share of total uptake, and FC would then not be a true upper limit of available water. To investigate if FC can be considered an efficient soil physical quantity to characterize soil water availability we used information of unsaturated hydraulic properties (retention and hydraulic conductivity) of 8 soil profiles in Brazil. Using the hydrological model SWAP we estimated FC based on pressure head and bottom flux criteria and evaluated water uptake by pasture and maize from the soil drier than FC (hence: from the “available water” pool between FC and permanent wilting point) as well as from the water held at tensions between saturation and FC. Results show a considerable (10–50%) fraction of transpired water is taken up from the soil at water contents above FC, making FC a questionable quantity to truly estimate crop available water and casting doubt on the reliability of bucket-type soil water balance models.

Farm Level Assessment of Irrigation Performance for Dairy Pastures in the Goulburn-Murray District of Australia by Combining Satellite-Based Measures with Weather and Water Delivery Information

Pasture performance of 924 dairy farms in a major irrigation district of Australia was investigated for their water use and water productivity during the 2015-2016 summer which was the peak irrigation period. Using satellite images from Landsat-8 and Sentinel-2, estimates of crop coefficient (Kc) were determined on the basis of a strong linear relationship between crop evapotranspiration (ETc) and vegetation index (NDVI) of pasture in the region. Utilizing estimates of Kc and crop water requirement (CWR), NDVI-dependent estimates of Irrigation Water Requirement (IWR) were derived based on the soil water balance model. In combination with daily weather information and seasonal irrigation water supply records, IWR was the key component in the understanding of current irrigation status at farm level, and deriving two irrigation performance indicators: (1) Relative Irrigation Water Use (RIWU) and (2) Total Irrigation Water Productivity (TIWP). A slightly higher proportion of farm irrigators were found to be either matching the irrigation requirement or under-watering (RIWU ≤ 1.0). According to TIWP, a few dairy farms (3%) were found to be in the category of high yield potential with excess water use, and very few (1%) in the category of limited water supply to pastures of high yield potential. A relatively high number of farms were found to be in the category where excess water was supplied to pastures of low-medium yield potential (27%), and farms where water supply compromised pastures with a sub-maximal vegetation status (15%). The results of this study will assist in objectively identifying where significant improvement in efficient irrigation water use can be achieved.

Satellite Observations of Regional Drought Severity in the Continental United States Using GRACE-Based Terrestrial Water Storage Changes

Drought monitoring is important for characterizing the timing, extent, and severity of drought for effective mitigation and water management. Presented here is a novel satellite-based drought severity index (DSI) for regional monitoring derived using time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE). The GRACE-DSI enables drought feature comparison across regions and periods, it is unaffected by uncertainties associated with soil water balance models and meteorological forcing data, and it incorporates water storage changes from human impacts including groundwater withdrawals that modify land surface processes and impact water management. Here, the underlying algorithm is described, and the GRACE-DSI performance in the continental United States during 2002–14 is evaluated. It is found that the GRACE-DSI captures documented regional drought events and shows favorable spatial and temporal agreement with the monthly Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM). The GRACE-DSI also correlates well with a satellite-based normalized difference vegetation index (NDVI), indicating sensitivity to plant-available water supply changes affecting vegetation growth. Because the GRACE-DSI captures changes in total terrestrial water storage, it complements more traditional drought monitoring tools such as the PDSI by providing information about deeper water storage changes that affect soil moisture recharge and drought recovery. The GRACE-DSI shows potential for globally consistent and effective drought monitoring, particularly where sparse ground observations (especially precipitation) limit the use of traditional drought monitoring methods.

Ecohydrological role of biological soil crusts across a gradient in levels of development

AbstractThough biological soil crusts (biocrusts) form abundant covers in arid and semiarid regions, their competing effects on soil hydrologic conditions are rarely accounted for in models. This study presents the modification of a soil water balance model to account for the presence of biocrusts at different levels of development (LODs) and their impact on one‐dimensional hydrologic processes during warm and cold seasons. The model is developed, tested, and applied to study the hydrologic controls of biocrusts in the context of a long‐term manipulative experiment equipped with meteorological and soil moisture measurements in a Colorado Plateau ecosystem near Moab, Utah. The climate manipulation treatments resulted in distinct biocrust communities, and model performance with respect to soil moisture was assessed in experimental plots with varying LOD as quantified through a field‐based roughness index (RI). Model calibration and testing yielded excellent comparisons to observations and smooth variations of biocrust parameters with RI approximated through simple regressions. The model was then used to quantify how LOD affects soil infiltration, evapotranspiration, and run‐off under calibrated conditions and in simulation experiments with gradual modifications in biocrust porosity and hydraulic conductivity. Simulation results show that highly developed biocrusts modulate soil moisture nonlinearly with LOD by altering soil infiltration and buffering against evapotranspiration losses, with small impacts on run‐off. The nonlinear and threshold variations of the soil water balance in the presence of biocrusts of varying LOD helps explain conflicting outcomes of various field studies and sheds light on the ecohydrological role of biocrusts in arid and semiarid ecosystems.

Evaluation of the FAO Aqua-Crop model for Durum wheat (Triticum durum Desf.)on the eastern Algeria under semi-arid conditions

The relative yield decline that is expected under specific levels of water stress at different moments in the growing period is estimated by integrating the FAO Ky approach in the soil water balance model BUDGET. FAO recently developed a water-driven model (Aqua-Crop) for use as a decision support tool in planning and scenario analysis in different seasons and locations. The Aqua Crop model was evaluated with experimental data collected during three cropping seasons; the field experiments were conducted in Setif, Algeria. The objective of the study is to quantify the water stress based on estimation of evapo-transpiration by Aqua Crop model in Durum wheat under stressed conditions.The results of this study proved the efficiency of the Aqua Crop model to quantify the water stress. Total water stress during three cropping seasons (2010-2013) ranged between 0.15 (15%) at Double ridges to anthesis stage to 0.56 (56%) at Anthesis to maturity stage. The AquaCrop model can adequately quantify water stress and can be used to explore management options to improve wheat water productivity.

SIMANIHOT: A PROCESS-BASED MODEL FOR SIMULATING GROWTH, DEVELOPMENT AND PRODUCTIVITY OF CASSAVA

ABSTRACT The objective of this study was to propose a model, named Simanihot, for simulating growth, development and yield of tuberous roots in cassava, with a choice of two soil water balance models. The model works on a day time step and is calibrated for five cassava cultivars (Fepagro –RS 14, Estrangeira, Cascuda, Sao Jose e Paraguaia), with different branching habits and different purpose of use (pasture, food and industry). The model has a graphical interface, where the user can choose one out of two soil water balance models, depending upon the number of known soil variables and details the user wants to know about soil water content.

Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance model

Abstract: In this study, an approach that integrates airborne imagery data as inputs was used to improve the estimation of soil water deficit (SWD) for maize and sunflower grown under full and deficit irrigation treatments. The proposed model was applied to optimize the maximum total available soil water (TAWr) by minimizing the difference between a water stress coefficient ks and crop water stress index (1-CWSI). The optimal value of maximum TAWr was then used to calibrate a soil water balance model which in turn updated the estimation of soil water deficit. The estimates of SWD in the soil profile of both irrigated maize and sunflower fields were evaluated with the crop root zone SWD derived from neutron probe measurements and the FAO-56 SWD procedure. The results indicated a good agreement between the estimated SWD from the proposed approach and measured SWD for both maize and sunflower. The statistical analyses indicated that the maximum TAWr estimated from CWSI significantly improved the estimates of SWD, which reduced the mean absolute error (MAE) and root mean square error (RMSE) by 40% and 44% for maize and 22% for sunflower, compared with the FAO-56 model. The proposed procedure works better for crops under deficit irrigation condition. With the availability of higher spatial and temporal resolution airborne imagery during the growing season, the optimization procedure can be further improved. Keywords: soil water deficit, soil water balance model, airborne imagery, total available water, CWSI, deficit irrigation DOI: 10.3965/j.ijabe.20171003.3081 Citation: Zhang H H, Han M, Chavez J L, Lan Y B. Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance model. Int J Agric & Biol Eng, 2017; 10(3): 37–46.

Using the FAO dual crop coefficient approach to model water use and productivity of processing pea (Pisum sativum L.) as influenced by irrigation strategies

Aiming at improved knowledge on water use, productivity and irrigation scheduling of processing pea, the soil water balance model SIMDualKc was calibrated and validated using field data observed in two farmers’ fields in a wet and a dry year. The model uses the dual crop coefficient approach for partitioning crop evapotranspiration into crop transpiration and soil evaporation. Calibration was performed by minimizing differences between measured and simulated soil water content with a root mean square error representing 2% of the measured mean. The calibrated basal crop coefficients for the initial, mid-season and end-season were respectively 0.15, 1.15 and 1.10. Pea commercial yield (5084–8197kgha−1), obtained from the total yield using industry textural and quality criteria, was influenced by climatic conditions and the harvesting date. Using the global water-yield function with Ky=1.15 and the actual crop transpiration computed with SIMDualKc, the fresh and commercial yields were estimated with errors smaller than 3.5%. Water productivity relative to the commercial yield varied 1.51–2.67kgm−3, mainly depending on the yield achieved rather than on water use. Results from the economic water productivity ratio (EWPR), which compares the commercial yield value with the corresponding production costs, varied 1.07–1.82. Because irrigation costs were a small fraction of the total costs, EWPR values mainly varied with the commercial yield and less with irrigation costs. Irrigation scheduling alternatives for wet and dry years showed that water saving is achievable without considerably affecting peas’ yield and economic results. Results show that the SIMDualKc model is appropriate to support irrigation advising.

Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties

Methodologies based on earth observation remote sensing allow for a precise estimation of actual water requirements for irrigated crops across large areas. In spite of the many number of experiments using or analyzing the relationship between the basal crop coefficient (Kcb) and the soil adjusted vegetation index (SAVI) for maize, the development of new maize hybrid varieties with modifications related to canopy architecture suggest a possible change of the leaf area index (LAI) for maximum Kcb and its relationship with the SAVI or other vegetation indices. In addition, we noted a lack of analysis of these relationships for cultivated soybean. The objective of this paper is to analyze the Kcb, SAVI and LAI relationships in maize and soybean based on the non-linear relationships proposed by Choudhury et al. (1994). In addition, we propose a modification of the Choudhury et al. (1994) approach based on field-based experimental evidence of a minimum Kcb greater than 0. For sites with limited field data, we also analyze the utility of a simple linear regression based on the Kcb and SAVI values for bare soil and maximum Kcb values. The resulting Kcb-SAVI relationships are assimilated into a remote sensing based soil water balance model. The results of the model are analyzed in terms of irrigation requirements and crop evapotranspiration (ETa) for 11 growing seasons in two fields cultivated with irrigated and rain-fed maize and soybean in eastern Nebraska. Comparisons of measured and modelled ETa values indicate a good agreement, with RMSE lower than 0.7mmd−1 for weekly averaged values. The comparison of actual irrigation applied and irrigation requirements indicate the central pivot systems could not supply adequate water in some growing seasons with higher demands.

Development of an Irrigation Scheduling Software for Sugarcane

Irrigation is vital for sustainable sugarcane production in rainfall-deficient areas. Efficient use of irrigation water remains a major concern because of increasing competition for water and a pressing need to improve productivity. A decision-making tool for the management of different irrigation systems at farm level has been developed to optimize irrigation water use, based on soil water balance and crop water satisfaction models. The software is GIS-based, integrating the biophysical factors related to irrigation at farm level, and has been designed to enable unbiased decision-making in irrigation management. Based on crop susceptibility to water stress, a priority ranking was produced for irrigation application at times of water scarcity. The software calculates soil water deficit from meteorological and soil data and subsequently works out irrigation water requirements. The output is in the form of recommendations for irrigation, giving priorities and water doses. The user can easily visualize the soil water deficit in time or space. The software has been successfully tested on four sugar estates. Feedback has been positive, and training has been provided to several potential users.

Adaptability to future climate of irrigated crops: The interplay of water management and cultivars responses. A case study on tomato

In the context of climate change strategies are needed towards sustainable agricultural production. The aim of this study is to identify crop adaptation options to face the expected changes in water availability by exploiting the existing intra-specific biodiversity of the tomato crop and accounting for irrigation management and the hydrological properties of soils. The biophysical dimension of crop adaptation is therefore addressed. A study is presented examining an irrigated district in southern Italy. Using as a climatic reference the period 1961–90 and as a future climate the period 2021–2050, a soil water availability indicator was determined by a soil water balance model, at optimal irrigation and at different deficit irrigation strategies, in 23 soil units. For five tomato cultivars, hydrological requirements were determined by means of yield response functions to soil water availability. Cultivar-specific hydrological requirements were evaluated against the soil water availability indicator to determine probabilities of adaptation of each cultivar. These cultivars are not currently being grown in the study area so their potential spatial distribution in the study area was estimated. For instance, with 60% of optimal irrigation, two cultivars were assessed as having probabilities of crop adaptation larger than 0.89, in 90% and 62% of the area. In the future climate, with limited water resources, a proper choice and combination of cultivars, irrigation strategies and soils would allow to maintain the current production system in a large part of the study area.

Including the lateral redistribution of soil moisture in a supra regional water balance model to better identify suitable areas for tree species

To assess suitable areas for species, plant ecologists need accurate spatial information about available water for plants. Despite the recognized importance of topography in controlling soil moisture patterns, existing maps do not account for the redistribution of water through lateral fluxes. We included lateral fluxes in a GIS-based soil water balance model with the aim of evaluating the influence of lateral fluxes on soil moisture patterns and their importance to explain tree species distribution at regional scale. We used hydrological knowledge about lateral fluxes to map the distribution of monthly average soil moisture over the 1961–1990 period, for a 43,000-km2 area in northeastern France. We then compared the ability of soil water estimated with or without lateral fluxes to explain the distribution of 19 common tree species. Spatial patterns significantly change when lateral fluxes are included in the model, with both large-scale effects due to variations in climate and soil properties, and local effects due to topography. The lateral redistribution given by the model revealed from 5% to 25% less water on the crests compared to in the valleys for metamorphic, sand and sedimentary bedrocks. Most of the tree species distributions studied were better explained when lateral fluxes were taken into account. Estimating soil moisture dynamics improves the ability to determine suitable areas for species at the landscape scale. It has major implications in the current climate change context owing to the potential to delineate topographic refugia or areas where species could colonize.