Daily Soil Water Balance Research Articles

DFEAT: A multifaceted yearly Drought FEature Assessment Tool from daily soil water content

The characterization of yearly drought events represents a key information for conducting impact assessments and forecasting future threats, and usually relies on a single index of duration or severity. Mostly based on daily soil or atmospheric water balances, the derivation of key drought facets is not yet standardized or embedded in a single tool, thus limiting intercomparisons between studies. We developed DFEAT as a fully-automated tool designed to characterize yearly drought features, based on any simulated/observed/remotely sensed soil water content time series. We provide here an application assessment performed with the Keetch-Byram Drought Index (KBDI) as a standard daily soil water model over a 60-year period and covering the Mediterranean aridity gradient in Lebanon (Middle-East) experiencing humid to semi-arid climate conditions. We computed and tested 19 drought features related to duration, severity, onset, offset, drying and wetting rates, driest peak day, and rainfall pulses across three soil water desiccation thresholds. For our study area, we revealed the uncorrelated specificities of 6 features, allowing to regionally discriminate between mountainous Mediterranean climate experiencing shorter drought duration (45 days), later onset (Day of the Year = 198), less rainfall pulses intensities (3.35 mm), and slower drying (1.68 mm/day) and wetting (−2.72 mm/day) rates, but similar offset date (Day of the Year = 356) compared to the coast. DFEAT also captured regions with prolonged Multi-Year Droughts not fully refilling field capacity under arid bioclimate reaching up to 22 years. We demonstrate here the applicability of DFEAT across water-limited bioclimates and the non-correlation between drought features with contrasted agro-ecological impacts.

Water use efficiency and water productivity of aerobic rice under drip irrigation and fertigation system by using daily soil water balance

Water use efficiency and water productivity of aerobic rice under drip irrigation and fertigation system by using daily soil water balance

Lettuce evapotranspiration and crop coefficients using eddy covariance and remote sensing observations

Lettuce (Lactuca sativa L.) is a high-value crop for irrigation districts in the low deserts of the USA Southwest. To ensure maximal crop quality, negligible soil salinity stress, minimal nutrient loss and reduced pathogen susceptibility, lettuce irrigation must meet, but not exceed, crop water use requirements. However, lettuce crop water use information is outdated in this region: prior studies were conducted at least four decades ago (1960–1980) and do not represent current varieties, management practices, and climate. To address this shortcoming, 12 commercial sites in Yuma, Arizona, USA were evaluated between 2016 and 2020 to update lettuce water use requirements and crop coefficients. The study measured crop evapotranspiration (ETc) using eddy covariance observations at eight iceberg and four romaine sites, where planting dates varied throughout the fall. Observed ETc and remote sensing data were used to model the daily soil water balance and derive crop coefficients: single (Kc), basal (Kcb), and soil evaporation (Ke). The analysis was supported by lettuce crop height estimates and fractional vegetative cover (fc) via remote sensing. Days to maturity averaged 75 ± 15 and 89 ± 12 days for romaine and iceberg, respectively, where season lengths increased as planting dates progressed from early fall to late winter. Average planting date for romaine sites was about 20 days earlier than average iceberg sites. When growing intervals are cast in heat units, dependence on crop type and time of planting was reduced. Average cumulative growing-degree-day and enhanced-degree-day metrics were 1133 ± 87 and 754 ± 48 °C-days, respectively. Seasonal lettuce ETc averaged 278 ± 24 mm. Cumulative irrigation applied, plus precipitation, averaged 355 ± 88 mm. Lettuce Kc for sites varied from 0.90 ± 0.13 to 1.19 ± 0.11 and Kcb from 0.20 ± 0.05 to 1.01 ± 0.11 for the initial and mid-season growth stages, respectively. These updates will help growers improve their irrigation efficiency for lettuce and provide important documentation needed by water managers.

Crop Water Productivity, Applied Water Productivity and Economic Decision Making

Increasing productive water use in agriculture is seen as paramount to meet future food demand with limited water supplies. The main objective of this paper is to gain a better understanding of the interrelated linkages between crop water productivity (CWP) and applied water productivity (AWP) as affected by irrigation management decisions in order to assess the impact of economic decision making on CWP and AWP under area-limiting and water-limiting conditions. A daily soil water balance mathematical programming model that explicitly models the impact of technology choice and stochastic weather on water use efficiency was used to study the interactions. The assumption is made that a rational decision maker will allocate water to maximize expected profits. The results showed that CWP is, to a large extent, unresponsive to increasing irrigation water applications, especially when water applications are approaching maximum potential crop yields. The difference between optimal crop yields for the area-limiting and water-limiting scenarios is small, which shows that the portion of water production function that is relevant for economic decision making is small and falls within the unresponsive range of CWP changes. Profit maximizing decision makers will not try to maximize CWP or AWP since these objectives will result in profit losses.

Evapotranspiration characteristics and soil water balance of alfalfa grasslands under regulated deficit irrigation in the inland arid area of Midwestern China

Drought has been a major limiting factor affecting agricultural production in the world. Accurately quantitative analysis of the dynamic changes of evapotranspiration and soil water balance is very important for effectively managing water resources and improving water use efficiency under water scarcity. Soil water balance for perennial forage is more complex than the annuals due to stronger roots and periodic evapotranspiration. The objective was to explore the evapotranspiration characteristics and soil water balance of alfalfa (Medicago sativa L.) grasslands under border irrigation at different stand ages and irrigation treatments. A 3-yr field experiment with a full irrigation and 6 regulated deficit irrigation treatments was conducted, and growth-related indicators, soil evaporation and soil water dynamics were observed regularly. Daily evapotranspiration and soil water balance were computed using a modified dual-Kc model which is able to simulate evaporation and transpiration separately. The results showed that soil water simulated by the model and the measured value were in good agreement, and regression coefficients were higher than 0.6 and close to 1.0 in most cuts. The change trend of root zone water under deficit irrigation at single growth stages was similar to that under full irrigation. Under irrigation, the transpiration was the main water loss of alfalfa grasslands. The daily actual evapotranspiration of alfalfa in the 1st cut was higher than 8.0 mm d−1 and even over 15.0 mm d−1 at the middle and later growth stages. In contrast, in the 2nd and 3rd cut, it was always less than 10.0 mm d−1. The daily actual evapotranspiration decreased significantly and immediately after cutting, and daily actual transpiration was reduced to less than 1.0 mmd−1. The change trend of daily actual evapotranspiration under deficit irrigation at single growth stages was also similar to that under full irrigation. The seasonal evapotranspiration could reach 800 mm and was reduced by deficit irrigation. The average proportion of soil evaporation to total evapotranspiration was 18%. With the decrease of irrigation amount, the evapotranspiration, transpiration and irrigation water compensation decreased, while evaporation remained relatively stable and the ratio of evaporation to evapotranspiration increased. A lower relative evapotranspiration deficit (0.041) was obtained under moderate deficit irrigation at the budding stage than those in other deficit cases (0.086 or over). In conclusion, in the arid and semi-arid areas, deficit irrigation could be applied to alfalfa grassland at the budding stage in alfalfa production.

Comparing the water use metrics of just-in-case, just-in-time and justified irrigation strategies using a scenario-based tool

Efficient water use is an important outcome of effective irrigation scheduling strategies. We developed a physically-based hydrology tool IrriSET (Irrigation Strategy Evaluation Tool) to simulate the performance of different scheduling strategies against three water use metrics - amount of irrigation used, drainage resulted from irrigation, and duration root zone soil water (crop soil water reservoir) was held within optimum pasture growth conditions during the irrigation season. IrriSET was tested on an irrigated dairy farm in Canterbury, New Zealand, simulating the daily soil water balance using observed and estimated data on rainfall, evaporation, root zone soil water holding capacity, irrigation supply reliability, irrigation infrastructure limitations (how quickly and how much irrigation could be applied per event), and irrigation application efficiency (designed versus actual application) from eighteen irrigation seasons for three scheduling strategies – ‘just-in-case', ‘just-in-time', and ‘justified’. Just-in-case, a rostered, supply-based irrigation strategy, resulted in the most irrigation applied per season and drainage generated, and the least duration of time soil water held in the optimum pasture growth condition. Soil water demand-based just-in-time, and demand- and weather-forecast based justified irrigation strategies resulted in similar water use metrics, though the latter consistently and marginally outperformed the former. Even during irrigation seasons with below normal rainfall and average irrigation supply conditions, though the demand and supply-based strategies used similar irrigation amounts, the latter held soil water in the optimal growth range longer than the former. A strategy that proactively manages irrigation based on supply (irrigation water availability and forecast rainfall) and demand (soil water condition) has been shown to be environmentally sustainable and positively influential of soil water availability within root zone, and thus productivity.

Assessing Irrigation Water Use with Remote Sensing-Based Soil Water Balance at an Irrigation Scheme Level in a Semi-Arid Region of Morocco

This study aims to evaluate a remote sensing-based approach to allow estimation of the temporal and spatial distribution of crop evapotranspiration (ET) and irrigation water requirements over irrigated areas in semi-arid regions. The method is based on the daily step FAO-56 Soil Water Balance model combined with a time series of basal crop coefficients and the fractional vegetation cover derived from high-resolution satellite Normalized Difference Vegetation Index (NDVI) imagery. The model was first calibrated and validated at plot scale using ET measured by eddy-covariance systems over wheat fields and olive orchards representing the main crops grown in the study area of the Haouz plain (central Morocco). The results showed that the model provided good estimates of ET for wheat and olive trees with a root mean square error (RMSE) of about 0.56 and 0.54 mm/day respectively. The model was then used to compare remotely sensed estimates of irrigation requirements (RS-IWR) and irrigation water supplied (WS) at plot scale over an irrigation district in the Haouz plain through three growing seasons. The comparison indicated a large spatio-temporal variability in irrigation water demands and supplies; the median values of WS and RS-IWR were 130 (175), 117 (175) and 118 (112) mm respectively in the 2002–2003, 2005–2006 and 2008–2009 seasons. This could be attributed to inadequate irrigation supply and/or to farmers’ socio-economic considerations and management practices. The findings demonstrate the potential for irrigation managers to use remote sensing-based models to monitor irrigation water usage for efficient and sustainable use of water resources.

Desempenho agronômico de mandioca de mesa manejada com irrigação e uso de cobertura plástica do solo

Although cassava is recognized for its high tolerance to drought, irrigation is showing satisfactory results. However, few studies have been carried out to determine the effects of soil cover, irrigation and the combination of both on crop development. Theobjective of this study was to determine the influence of irrigation and plastic soil cover on the agronomic performance of sweet cassava. The planting was done in beds, in thedouble row system with the stem cutingsimplanted vertically, with 0.60m between rows and 0.80 m between plants. The following treatments were applied: naked non-irrigated bedding, bedding covered with non-irrigated black polyethylene plastic, naked bedding with irrigation and bedding covered with irrigated black polyethylene plastic. Irrigation wasperformedby conventional sprinkling, based on the daily soil water balance at the effective depth of the cassava root system in the different stages of crop development. The characters evaluated were: shoot weight, root yield, starch percentage in the roots and time for cooking. The expression of the characters shoot weight, root yield and starch percentage in the roots wassignificantly influenced by irrigation managementandsoil cover. The individual use of irrigation and plastic soilcover technologies led to increases in root yieldof 55% and 13%, respectively, and when used together, root yieldincreased by 89%.

Spatiotemporal Assessment of Agricultural Drought Using a Cell-Based Daily Soil Water Analysis Model

This study developed a cell-based daily soil water analysis model (CellSW) for evaluating agricultural drought and calculated an agricultural drought index called the “Rainfall Effectiveness Index for Crop” (REIC). The model analyzed a daily soil water balance based on crop types, growth stages, soils, and climate. It adopted the rasterized daily rainfall, daily evapotranspiration, crop coefficient (by crop growth stage), and root depth as input parameters; it also consecutively generated the daily surface layers of the water balance items in each cell, such as the consumptive use, effective rainfall, available soil water, and irrigation requirements. The model was applied in a test area in Illinois and Iowa, targeting corn and soybeans; the soil water balance was analyzed during the growing period from 2000 to 2018. The model calculated the seasonal REIC, defined as the ratio of supply quantity (effective rainfall) to demand quantity (crop evapotranspiration). In addition, the accumulated REIC values were estimated. The REIC was confirmed to accurately reflect drought situations in the relevant areas, based on comparisons with drought records. The cell-based model can be applied to different types of cultivated crops, growth stages, and soil conditions without spatial and temporal limitations, even in mixed farming.

Water uptake dynamics for adult peach trees in a subtropical humid climate

Low-chill peach [Prunus persica (L.) Batsch] cultivars allow Florida growers to become competitive by offering fruits earlier than northern states for premium prices. Due to the predominance of sandy soils in Florida, irrigation is required to ensure fruit production in peaches. Available irrigation recommendations and peach crop coefficients (Kc) were determined in Mediterranean and temperate climates, and they can overestimate water demand in humid subtropical climates. Thus, a two-year study was conducted in Citra, FL, aiming to determine the water requirements and Kc values for four-year-old peach trees in humid subtropical conditions. A daily soil water balance and the crop evapotranspiration (ETc) was determined using soil volumetric water content recorded every 10 min. Five soil probes, each equipped with soil moisture sensors at 10, 20, 40, and 80 cm of soil depth representing soil depth layers of 0–15, 15–30, 30–60, and 60–90 cm, respectively placed under the tree canopy. The ratios of daily ETc and Penman-Monteith FAO-56 reference evapotranspiration were used to estimate Kc for phenological stages of adult (≥4-year-old) peach trees. A soil water depletion coefficient (Ks) was estimated obtaining a threshold of 25.8 % available soil water depletion before trees undergo water stress. Daily ETc ranged from 0.22 mm d−1 during dormancy to 3.65 mm d−1 during shoot development. Values of Kc for peach trees ranged from 0.30 during dormancy to 0.69 during fruit maturity. The use of peach tree Kc adapted for subtropical humid conditions reduce the estimated crop water requirements by 21 % compared to the Kc values reported in FAO-56 guidelines.

Monitoring groundwater heads and estimating recharge in multi-aquifer systems illustrated by an irrigated area in north-west Bangladesh

The impact of groundwater abstraction in multi-aquifer systems can be identified by monitoring variations of groundwater heads with depth and with time. Equally important are estimates of recharge to the groundwater system including contributions from irrigation. A case study from the Rajshahi Barind in Bangladesh illustrates the methodologies. Abstraction of groundwater from deep tubewells has resulted in substantial increases in agricultural production but also significant falls in groundwater heads in the aquifers. Monitoring of the groundwater heads at different depths and relating these to the lithology has indicated the formation of an additional water table in an intermediate aquifer; this leads to the conceptualisation of the aquifer system as two Units, Upper and Lower. Estimates of the potential recharge to the aquifer system are obtained from a daily soil water balance which is enhanced to include the representation of recharge from standing water in flooded ricefields. Detailed fieldwork, over a period of more than 2 years, includes daily records of groundwater heads, rainfall, temperature and hours of pumping for irrigation; information about the crops grown in the command area is also collected. Individual, but interconnected, conceptual and computational models for the two Units are developed. The outputs of the computational models show good agreement with measured groundwater head fluctuations. Using information from the computational models, the sustainability of the current abstraction patterns is considered.

Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices.

The rapid, accurate, and real-time estimation of crop coefficients at the farm scale is one of the key prerequisites in precision agricultural water management. This study aimed to map the maize crop coefficient (Kc) with improved accuracy under different levels of deficit irrigation. The proposed method for estimating the Kc is based on multispectral images of high spatial resolution taken using an unmanned aerial vehicle (UAV). The analysis was performed on five experimental plots using Kc values measured from the daily soil water balance in Ordos, Inner Mongolia, China. To accurately estimate the Kc, the fraction of vegetation cover (fc) derived from the normalized difference vegetation index (NDVI) was used to compare with field measurements, and the stress coefficients (Ks) calculated from two vegetation index (VI) regression models were compared. The results showed that the NDVI values under different levels of deficit irrigation had no significant difference in the reproductive stage but changed significantly in the maturation stage, with a decrease of 0.09 with 72% water applied difference. The fc calculated from the NDVI had a high correlation with field measurement data, with a coefficient of determination (R2) of 0.93. The ratios of transformed chlorophyll absorption in reflectance index (TCARI) to renormalized difference vegetation index (RDVI) and TCARI to soil-adjusted vegetation index (SAVI) were used, respectively, to establish two types of Ks regression models to retrieve Kc. Compared to the TCARI/SAVI model, the TCARI/RDVI model under different levels of deficit irrigation had better correlation with Kc, with R2 and root-mean-square error (RMSE) values ranging from 0.68 to 0.80 and from 0.140 to 0.232, respectively. Compared to Kc calculated from on-site measurements, the Kc values retrieved from the VI regression models established in this study had greater ability to assess the field variability of soil and crops. Overall, use of the UAV-measured multispectral vegetation index approach could improve water management at the farm scale.

Linking soil water balance with flood spatial arrangement in an extremely flat landscape

AbstractIn areas with very mild relief, water drains in a disordered way due to the lack of a developed drainage network, as it occurs in extremely flat sedimentary regions like the Argentine Pampas. The study analysed the flood spatial arrangements in 2014 by calculating landscape metrics and relating them to soil water balance. The study area is located at Del Azul creek lower basin (Pampa Ecoregion, Argentina). Daily soil water balances were obtained, and seven landscape metrics were calculated in 15 windows in five LandSat images, all along 2014, to explore the relationship between hydrological scenarios and spatial pattern summarized with principal component analysis. Water excess concentrated in winter (June and August); deficits were in late spring and summer (January and November), whereas the beginning of autumn (March) was an intermediate situation. Principal component 1 (44.7%) reflected area and shape metrics and correlated positively with water table level; principal component 2 (32.3%) summarized aggregation ones and was negatively associated with accumulated water excesses or deficits in previous 30 days and useful reserve. Both exhibited possible threshold‐driven behaviour. Internal heterogeneity between NW and SE zones within the study area coincided with the existence of ancient alluvial fans. The results highlight the peculiarities of the flood spatial patterns in regions with very mild relief, where landforms usually determine water flows.

Application of ET-NDVI-relationship approach and soil-water-balance modelling for the monitoring of irrigation performance of treed horticulture crops in a key fruit-growing district of Australia

ABSTRACTRemotely sensed data from Landsat-8 and Sentinel-2 were used to demonstrate the estimation of irrigation water requirement (ρ) for treed horticulture crops in an important irrigation district of Australia. Crop- and region-specific relationship between satellite-derived evapotranspiration (ET) and normalized difference vegetation index (NDVI) was combined with daily step soil water balance to investigate the performance of horticulture crops for their water use during the peak irrigation demand period (summer) over three years from 2014–15 to 2016–17. Relative irrigation water use (RIWU) as the key irrigation performance indicator was calculated by comparing the irrigation water supply (ψ) records and the ρ estimates. ψ and ρ of the treed horticulture crops showed a strong positive correlation (Coefficient of determination, R2 > 0.70; p < 0.001) for each of the three summer seasons investigated, indicating an overall consistency in irrigation pattern. However, the values of both ρ and ψ varied considerably at farm level over the seasons, highlighting the changing demand and supply of crop water over the years. Most farms remained within the optimal irrigation range (0.5–1.5 RIWU) over the seasons – 75% in 2014–15, 68% in 2015–16, and 80% in 2016–17. However, some farms were over-irrigated (>1.5 RIWU) – 12% in 2014–15, 5% in 2015–16, and 8% in 2016–17.

Actual evapotranspiration and crop coefficient of sweet orange during the initial development phase in the Rio Largo region, Alagoas

ABSTRACT: Determining actual crop evapotranspiration (ETa) is paramount for irrigation management. The principal measurement methods and physical models generally require crop and weather data that are not readily available. We determined the crop coefficient (Kc) of sweet oranges during the initial development stage and evaluated the performance of the Poulovassilis semi-empirical model coupled with a simple soil water balance for estimating the ETa. The ETa was inferred from the variation in the soil water content over time, measured by time-domain reflectometry. In the Poulovassilis model, the ETa is obtained by multiplying the crop evapotranspiration (ETc) by an adjustment coefficient (ca), which accounts for a reduction in the evapotranspiration caused by soil water depletion. Soil water storage was obtained using the daily and 10-day soil water balances, computed by considering inputs and outputs of water from the system. The empirical parameter, ca, was determined using inverse modeling. The optimal ca value obtained through inverse modeling was 0.05 and 0.03 for the daily and 10-day soil water balances, respectively. The model performed better for the daily soil water balance than the 10-day balance, with performance comparable with the other ETa models. Average Kc during the sweet orange initial crop stage was 0.85.

High-Throughput Phenotyping of Crop Water Use Efficiency via Multispectral Drone Imagery and a Daily Soil Water Balance Model

Improvement of crop water use efficiency (CWUE), defined as crop yield per volume of water used, is an important goal for both crop management and breeding. While many technologies have been developed for measuring crop water use in crop management studies, rarely have these techniques been applied at the scale of breeding plots. The objective was to develop a high-throughput methodology for quantifying water use in a cotton breeding trial at Maricopa, AZ, USA in 2016 and 2017, using evapotranspiration (ET) measurements from a co-located irrigation management trial to evaluate the approach. Approximately weekly overflights with an unmanned aerial system provided multispectral imagery from which plot-level fractional vegetation cover ( f c ) was computed. The f c data were used to drive a daily ET-based soil water balance model for seasonal crop water use quantification. A mixed model statistical analysis demonstrated that differences in ET and CWUE could be discriminated among eight cotton varieties ( p &lt; 0 . 05 ), which were sown at two planting dates and managed with four irrigation levels. The results permitted breeders to identify cotton varieties with more favorable water use characteristics and higher CWUE, indicating that the methodology could become a useful tool for breeding selection.

Soil fertilization transiently increases radial growth in sessile oaks but does not change their resilience to severe soil water deficit

The future climate is projected to become increasingly problematic for European forest ecosystems, likely leading to the decline of many tree species. Forest management must adapt to cope with the negative effects of these changes. Despite the close interactions between nutrients and water in plant physiology, very few studies have investigated the link between soil fertility and tree response to soil water availability and vapour pressure deficit. The objective of this study was to test whether fertilization would modify forest tree resilience to soil water deficit.The potential impact of fertilization on trees during soil water deficit was assessed in a fertilization experiment carried out on sessile oaks. Three fertilization treatments (NCa, NPKCaMg and an unfertilized control) were applied to 40-year-old oaks that were cored almost 40 years later. The responses to drought in the fertilized and control trees were compared by analysing the radial growth chronologies following two complementary approaches. Firstly, the relationships between radial growth and inter-annual climate variations were investigated through dendroclimatic modelling including water deficit indices computed with the daily soil water balance model Biljou©. Secondly, resistance, recovery and resilience to drought-induced crises were evaluated from tree-ring width and compared among treatments. In addition, the carbon isotope composition (δ13C) of the tree rings was measured to evaluate potential differential gas-exchange processes between fertilized and control trees.Fertilization had an immediate, strong positive effect on oak growth which disappeared after nine years. NCa and NPKCaMg fertilizations had similar effects, suggesting that adding P, K and Mg did not increase radial growth. Whatever the treatment, ring width variations appeared to be identically constrained by climate, especially by the summer water deficits of the current and previous years. Tree resistance to soil water deficit was negatively affected by the severity of the drought event but did not significantly differ between control and fertilized trees. Tree resilience was not affected by fertilization and remained stable across crises. The tree-ring δ13C clearly increased during the severe 1976 water deficit but did not vary among treatments. We discuss the possible mechanisms involved in changes in growth and the lack of any significant effect of fertilization on resilience to drought and conclude that, under the relatively dry conditions and moderately poor soil fertility of our study site, fertilization could temporarily stimulate aboveground growth without inducing imbalances that would modify resilience and resistance to severe drought episodes.

Putah Creek hydrology affecting riparian cottonwood and willow tree survival.

Creating or recruiting new riparian forests to improve Lower Putah Creek (LPC) ecosystem functions is challenging under the modified stream flow regime developed after historic gravel mining and installation of Monticello Dam upstream. Hydrologic connectivity between riparian trees, shallow groundwater, and the low flow channel is essential towards maintaining these forests and related habitats through the annual summer and multi-year drought periods typical in this Sacramento Valley region of California. Despite increased average summer flows, significant mature cottonwood and willow tree mortality along the LPC riparian areas below the Putah Creek diversion dam in 2014 raised concerns over the soil and hydrologic factors affecting riparian vegetation survival. A forensic analysis was conducted combining annual canopy coverage fractions and tree ring studies with daily soil-water balances, low flow records, and available groundwater level Information from the past few decades to determine the key hydrologic factors affecting riparian tree survival along the LPC. The 2011-2016 drought was linked with greater than prior average soil-water deficits in 2012-2015 and lower initial soil-water storage on March 1 of 2012 and 2014 that would be expected to stress the trees. However, such stress was not apparent in decreased tree ring spacing during this period from mature (40-50years old), deceased, and living trees. Tree canopy coverage declined dramatically (by as much as 50% as compared to the previous decade average) only in the summer of the 2014 despite a ~ 35% increase in average summer flows from 2011 to 2014. However, the regional water table aquifer levels declined at an average rate of ~ 35mm/day in 2014 (as compared to ~ 17mm/day in previous decade) and by several meters overall between 2011 and 2016 suggesting that deceased trees lacked access to the water table aquifer or lateral stream seepage. The increased rates of water table decline and overall depth may be associated with a large increase in adjacent irrigated almond orchard areas in 2014-2016. Knowledge of the dynamic hydrologic factors controlling sustainability of riparian trees should better inform and guide future tree restoration efforts along the LPC.

Coupling irrigation scheduling with solar energy production in a smart irrigation management system

In recent years, pressurized pipe networks have improved the efficiency of irrigation systems while substantially increasing their energy demand. The progressive rise in energy costs makes it difficult to maintain the profitability of agricultural holdings. Moreover, global warming is a serious problem that threatens the environment worldwide and low CO2 emission processes should be promoted. To address these issues, it is necessary to look for sustainable and more profitable alternatives for the agricultural sector. One of these new alternatives is the use of renewable energies for pumping irrigation water at farm level, particularly photovoltaic energy. Nevertheless, the instability of irradiation hinders its management for stand-alone photovoltaic installations. In this work, a real-time model called the Smart Photovoltaic Irrigation Manager (SPIM) is developed to synchronize the photovoltaic power availability with the energy required to pump the irrigation requirements of different sectors of irrigation networks. SPIM consists of different modules to calculate the key management variables of the photovoltaic irrigation system: the daily irrigation requirements, the hydraulic behavior of the irrigation network, the instantaneous photovoltaic power production and the daily soil water balance. The lack of photovoltaic energy during daylight hours on any day of the irrigation season to supply the daily required amount of water is balanced with either the water stored in the soil or by extending the duration of the irrigation events in the following days when necessary. SPIM has been applied to simulate the management of photovoltaic irrigation in a real olive orchard in Southern Spain during the 2013 irrigation season. The results showed that the proper management of the photovoltaic irrigation system provided enough water to satisfy crop irrigation requirements throughout the irrigation season and avoided the emission of 1.2 tn CO2 eq using only the energy generated by solar panels.

Simulation of soil water balance and partitioning of evapotranspiration of maize grown in two growing seasons in Southern Brazil

ABSTRACT: The objective of this study was to simulate the variation of the available soil water during maize crop growth, in two different sowing times (first and second growing season), using a drip irrigation system. The treatments consisted of different irrigation strategies (full to deficit). The SIMDualKc simulation model was used to determine the daily soil water balance and crop evapotranspiration using the dual crop coefficient approach. Soil, climate, crop and irrigation parameters were used as input data. Two experiments were carried out in a rainout shelter composed of two metallic structures (16x10m) in the city of Santa Maria, Rio Grande do Sul, Brazil, during 2010/11 (second crop, season 1) and 2011/12 (first crop, season 2) growing seasons, under no-tillage system. The simulations showed that all the irrigation management strategies used in season 2 resulted in soil water deficit, while only two strategies showed deficit in season 1. Results showed good agreement between observed and simulated soil water data, with an R2 ranging from 0.86 to 0.99 and the root mean square error ranging from 2.7 to 5.6% of the total available water for seasons 1 and 2, respectively. The observed results of water balance showed that maize grown in season 2 presented higher water consumption compared to season 1, due to the higher atmospheric demand of season 2. The SIMDualKc model allowed the partitioning of crop evapotranspiration into soil evaporation and crop transpiration, demonstrating that the vegetative growth subperiod presented the greatest differences between the two seasons compared to the others growth phases.