Change In Moisture Storage Research Articles

Seasonal dynamics and spatial patterns of soil moisture in a loess catchment

Abstract. The spatial and seasonal patterns in soil moisture and the processes controlling them in semi-arid landscapes are not well understood. Loess landscapes minimize any confounding effects of variation in soil characteristics and are thus ideal for studying topographic influences on soil moisture in drylands. In this study, volumetric soil moisture was monitored monthly for 5.5 years at 20 cm intervals between the surface and 5 m depth at 89 sites across a small (0.43 km2) catchment on the Chinese Loess Plateau. The median soil moisture was computed for each month and depth for each monitoring site as a measure of the typical soil moisture conditions. Seasonal changes in soil moisture were mainly concentrated in the shallow (0–100 cm) soil, with a clear seasonal separation between wet conditions in October–March and dry conditions in May–July, even though precipitation is highest in July–August. Soil moisture was higher on the northwest-facing slopes due to increased drying from solar radiation on the southeast-facing slopes. This effect of slope aspect was greater between October and March, when the zenith angle of the sun was lower and the aspect-dependent difference in solar radiation reaching the surface was larger. The wetter, northwest-facing slopes were also characterized by larger annual soil moisture storage changes. Soil texture was nearly uniform across both slopes, and soil moisture was not correlated with the topographic wetness index, suggesting that variations in evapotranspiration dominated the spatial pattern of soil moisture in shallow soils under both wet and dry conditions. Water balance calculations indicate that over 90 % of the annual precipitation was seasonally cycled in the soil between 0 and 300 cm, suggesting that only a minor fraction infiltrates to groundwater and becomes streamflow. Our findings may be broadly applicable to loess regions with monsoonal climates and may have practical implications for catchment-scale hydrologic modeling and the design of soil moisture monitoring networks.

Quantifying basin-scale changes in groundwater storage using GRACE and one-way coupled hydrological and groundwater flow model in the data-scarce Bandung groundwater Basin, Indonesia

Assessing basin-scale groundwater storage changes is often difficult when groundwater table data are scarce. In this study, we quantify the groundwater storage changes by using the Wflow_sbm hydrological model coupled with the MODLOW groundwater model in the data-scarce area of the Bandung groundwater basin, Indonesia. The soil moisture storage change calculated by Wflow_sbm plus the groundwater storage change calculated by MODFLOW is compared to the water storage change estimated by the GRACE satellite between 2005 and 2015. The calculated cross-correlation coefficient is 0.502, and 62.1% of the simulated water storage change falls within GRACE's estimated uncertainty bounds. The important context in the water storage comparison are GRACE temporally local time-lags, data gaps in GRACE datasets, and differences in model seasonal performance and analyzed domain characteristics. The two latter factors highlight the importance of considering local groundwater-related information over large-scale global datasets in basin-scale groundwater storage change assessment. Based on the groundwater flow model, the current predicament of groundwater abstraction in the Bandung groundwater basin is highly unsustainable for future groundwater uses. On average, the groundwater storage in the study area is dwindling at the rate of 87 million m3/year between 2005 and 2018, dominantly a consequence of groundwater abstraction, whose effect is rippled to further impact the whole groundwater flow regime. Agreed by the situation shown by the limited data, the simulated groundwater table drawdown, spatially, is found to be locally and non-uniformly distributed. The capability of a one-way coupled hydrological and groundwater model to investigate basin-scale groundwater storage change, with comparable estimates to the GRACE dataset, unravel the opportunity of using such methods to estimate the behavior of future groundwater storage dynamics under the changing anthropogenic and climatic factors in catchment-scale studies.

Effect of Coffee Ages and Shade Types on Soil Moisture and Soil N, P, K Availability in UB Forest

Water and nutrients is important for plant which has its characteristics. This study has been carried out in the UB (Brawijaya University) forest about soil moisture content during rainy and dry seasons, Total-N, -P, -K from litter on different types of shade and age of coffee plants, and their effect on soil Available-N, -P, and -K. There are P1 (control), P2 (4-year-coffee + pine), P3 (7-year-coffee + pine), P4 (4-year-coffee + mahogany), and P5 (7-year-coffee + mahogany). These treatments affected to total soil moisture storage, Total-N, -P, -K of litter, and Available-N, -P, -K in the soil. The soil moisture storage change between rainy and dry seasons was 36.97 mm. The highest Total-N, -P, and -K of litter was 11.00 kg ha-1 y-1 at P3, 1.06 kg ha-1 y-1 at P2, and 4.35 kg ha-1 y-1 at P3, which was inconsistently associated with high soil nutrients. The highest Total-N was 0.40 (0-20 cm), 0.27 (20-40 cm), 0.30% (40-60 cm) at P4, Available-K was 1.69 (0-20 cm), 1.64 (20-40 cm), 1.87 cmol kg-1 (40-60 cm) at P5, and Available-P was 15.21 (0-20 cm), 14.06 (20-40 cm), 12.64 mg kg-1 (40-60 cm) at P1.

A novel approach to analyze uncertainties and complexities while mapping groundwater abstractions in large irrigation schemes

While determining the water balance for large irrigation schemes, coping with complexities and uncertainties in estimation of groundwater (GW) abstraction is still a challenge. On other hand, estimating GW abstraction is of paramount importance to ensure the proper management of surface and GW resources. Although, there are number of well-known methods exist to map GW abstraction, utilization-factor (Uf) is considered as a reliable method. However, at large scales, tubewells utilization time required for Uf method is difficult to retrieve as large and small tubewells are governed under different rules. Geo-informatics is another emerging approach being used to estimate GW abstraction, however, there are several complexities and uncertainties involved in characterizing GW abstraction using satellite remote sensing imagery that leads to inaccurate end results. In current study, in-situ GW measurements were performed to calibrate and validate the GW abstraction estimated from geo-informatics approach at Lower Bari Doab Canal (LBDC) command area of the Indus basin of Pakistan. For in-situ measurements, an intensive tubewell survey was conducted at a grid size of 1 km at 30 locations situated at head, middle and tail end reaches of the LBDC. For the geo-informatics approach used in this study, GW abstraction is considered as a difference of actual evapotranspiration (ETa) from net canal water use and effective rainfall after satisfying soil moisture storage changes. Results of calibration of geo-informatics approach compared with the in-situ measurements showed R2 of 0.89, 0.81 and 0.79 at head, middle and tail end reaches, respectively. Intra-grid annual comparison of in-situ measurements showed that tubewells were being governed by different rules and thus yielded different abstraction within a grid ranging from 854 mm (±105) at head, 742 mm (±220) at middle and 649 mm (±244) at tail grids. Statistical analysis showed that annual GW abstraction by in-situ measurements at head 814 mm (±52), middle 769 mm (±44) and tail 688 mm (±56) end reaches varied significantly at a confidence interval of 95%. The spatial mapping by geo-informatics showed that farmers’ fields situated at proximity of head end reaches utilize 4% and 9% extra water than from those placed at middle and tail end reaches, respectively. The inequity of GW abstraction in LBDC command area highlighted in this study requires immediate intervention of policy makers for sustainable GW management.

Streamflow partitioning using the Budyko framework in a northern glaciated watershed under drought to deluge conditions

We use the Budyko framework to examine streamflow changes due to climate variation and human activities in the Mauvais Coulee Basin, a 1002 km2 sub-basin that contributes streamflow to Devils Lake, a terminal lake that has experienced catastrophic flooding over the past three decades. The basin lies within the northern glaciated prairies, contains innumerable wetland complexes that follow fill-spill hydrological principles, has undergone extensive land use change to support dryland farming, and has experienced a drought to deluge hydroclimatic transition over the last century. We implement the Budyko framework to partition the runoff increase to the lake between its climatic or human components. Initial results attribute 45% of the streamflow increase to climate factors, and 55% to human activities. Implementation of the Budyko framework to examine streamflow partitioning, however, rests upon a series of assumptions that are usually not directly verified. We then examine each Budyko framework assumption to determine its suitability for our study site and study period. None of the required assumptions are fully satisfied. Our study site and study period encompass two distinct hydroclimatic modes, contain no clear single inflection point separating baseline and altered periods, experience root zone soil moisture storage changes during the study period, and exhibit a non-stationary precipitation-streamflow relationship during the transitional period between the two hydroclimatic modes. Streamflow attribution produced by the standard application of the Budyko framework is not applicable to our study site or study period. We recommend that local-scale investigations of streamflow partitioning based upon the Budyko framework be more intentional in verifying model assumptions as a standard practice in implementing the method.

Large-scale vegetation responses to terrestrial moisture storage changes

Abstract. The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

Reconstructing annual groundwater storage changes in a large-scale irrigation region using GRACE data and Budyko model

A two-parameter annual water balance model was developed for reconstructing annual terrestrial water storage change (ΔTWS) and groundwater storage change (ΔGWS). The model was integrated with the Gravity Recovery and Climate Experiment (GRACE) data and applied to the Punjab province in Pakistan for reconstructing ΔTWS and ΔGWS during 1980–2015 based on multiple input data sources. Model parameters were estimated through minimizing the root-mean-square error between the Budyko-modeled and GRACE-derived ΔTWS during 2003–2015. The correlation of ensemble means between Budyko-modeled and GRACE-derived ΔTWS is 0.68 with p-value <0.05. The ΔGWS was reconstructed by subtracting soil moisture storage change from the Budyko-modeled ΔTWS and was validated (i.e., r=0.74, p-value<0.05) against well observations during the pre-GRACE period (i.e., 1985–1994). The negative values of the cumulative sum of the reconstructed ΔGWS during 1980–2015 (i.e., −13.6±9.7cm) indicate that the aquifer in Punjab has experienced depletion. The estimated depletion rate is −0.3±0.2cm/year and it has a negative correlation (i.e., r=−0.70, p-value<0.0001) with the total number of tube wells installed in Punjab. The integration of the developed Budyko model with GRACE data provides a new way for evaluating long-term groundwater depletion in large-scale irrigation regions with parsimonious models.

Vegetation regulation on streamflow intra‐annual variability through adaption to climate variations

AbstractThis study aims to provide a mechanistic explanation of the empirical patterns of streamflow intra‐annual variability revealed by watershed‐scale hydrological data across the contiguous United States. A mathematical extension of the Budyko formula with explicit account for the soil moisture storage change is used to show that, in catchments with a strong seasonal coupling between precipitation and potential evaporation, climate aridity has a dominant control on intra‐annual streamflow variability. But in other catchments, additional factors related to soil water storage change also have important controls on how precipitation seasonality propagates to streamflow. More importantly, use of leaf area index as a direct and indirect indicator of the above ground biomass and plant root system, respectively, reveals the vital role of vegetation in regulating soil moisture storage and hence streamflow intra‐annual variability under different climate conditions.

Balanço hídrico da cultura da mamona sob condições de sequeiro

O estudo dos componentes do balanço de água no solo é essencial para se compreender sua dinâmica, fornecendo subsídios para o manejo agrícola e otimização do uso de água. O presente trabalho objetivou determinar os componentes do balanço de água em solo cultivado com mamona sob condições de sequeiro. Para tal foram instalados, numa área de 4 ha da Fazenda Experimental Chã do Jardim, do Centro de Ciências Agrárias da UFPB, Areia, PB (6o 58' S, 35o 41' W e 620 m) três sítios tensio-neutrônicos cada um contendo um tubo de acesso para a sonda de nêutrons até a profundidade de 1,60 m e oito tensiômetros nas profundidades de 0,10; 0,20; 0,30; 0,40; 0,60; 0,80; 1,20 e 1,60 m, além de um pluviógrafo para medir a precipitação. Com vista à determinação da condutividade hidráulica saturada do solo, foram realizados ensaios de infiltração na superfície e nas profundidades de 0,20; 0,40; 0,60 e 0,80 m. A evapotranspiração da mamona seguiu as variações da precipitação e teve valor médio de 2,43 mm d-1, perfazendo o total de 342,52 mm. As variações do armazenamento de água no solo seguiram as variações da precipitação pluvial e o fluxo de água na base do solo (ascensão capilar ou drenagem) tiveram valores muito pequenos.

GRACE, GLDAS and measured groundwater data products show water storage loss in Western Jilin, China

Water storage depletion is a worsening hydrological problem that limits agricultural production in especially arid/semi-arid regions across the globe. Quantifying water storage dynamics is critical for developing water resources management strategies that are sustainable and protective of the environment. This study uses GRACE (Gravity Recovery and Climate Experiment), GLDAS (Global Land Data Assimilation System) and measured groundwater data products to quantify water storage in Western Jilin (a proxy for semi-arid wetland ecosystems) for the period from January 2002 to December 2009. Uncertainty/bias analysis shows that the data products have an average error <10% (p < 0.05). Comparisons of the storage variables show favorable agreements at various temporal cycles, with R(2) = 0.92 and RMSE = 7.43 mm at the average seasonal cycle. There is a narrowing soil moisture storage change, a widening groundwater storage loss, and an overall storage depletion of 0.85 mm/month in the region. There is possible soil-pore collapse, and land subsidence due to storage depletion in the study area. Invariably, storage depletion in this semi-arid region could have negative implications for agriculture, valuable/fragile wetland ecosystems and people's livelihoods. For sustainable restoration and preservation of wetland ecosystems in the region, it is critical to develop water resources management strategies that limit groundwater extraction rate to that of recharge rate.

Estimating soil moisture storage change using quasi-terrestrial water balance method

a b s t r a c t Soil moisture is a critical consideration for agriculture and hydrology especially in semi-arid regions. Like groundwater, soil moisture measurements may not always available in sufficient distributions for effective monitoring of agricultural operations. This paper presents a quasi-terrestrial water balance method, driven by common hydro-climatic data, to estimate soil moisture. The method is tested for the ≈152 000 km 2 floodplain region of Hai River Basin using 48 consecutive months (January 2003-December 2006) of data. Comparisons of the estimated and field-measured soil moisture storage and storage change show favorable agreements at monthly, seasonal yearly cycles. This suggests that the proposed method reliably detects soil moisture storage signal in the tested region. The analysis shows a narrowing soil moisture storage change in the study area. Further analysis indicates that the narrowing in soil moisture storage change is sustained by groundwater storage loss via irrigation. There is also storage loss to the atmosphere via irrigation-driven evapotranspiration. Apparently, storage gain occurs in summer while storage loss occurs in winter. However, an overall storage loss exists in the tested floodplain region of Hai River Basin.

Snowmelt runoff sensitivity analysis to drought on the Canadian prairies

AbstractThe Canadian prairies are subject to severe extended droughts that are characterized by warmer temperatures, lower precipitation, lower soil moisture and sparser vegetation than normal conditions. The physically based cold regions hydrological modelling platform (CRHM) provides a possible means to analyse the sensitivity of prairie snowmelt processes to drought. The model was tested against detailed observations from Creighton Tributary of the Bad Lake Research Basin, Saskatchewan for the 1974–1975 and 1981–1982 hydrological years and found to perform satisfactorily in reproducing snow accumulation and streamflow without parameter calibration. By lowering winter precipitation and raising winter air temperature from actual meteorological observations and by lowering fall soil moisture and vegetation height parameters, the resulting drought condition sensitivity of snow accumulation, snow cover duration, sublimation of blowing snow, evaporation, infiltration into frozen soils, soil moisture storage change, snowmelt runoff and streamflow discharge was estimated. Snow accumulation and snow cover duration were relatively insensitive to meteorological changes associated with drought because the suppression of blowing snow sublimation moderated reduced snowfall. Infiltration, soil moisture storage change and evaporation were also relatively insensitive to drought conditions. However, lower precipitation, higher air temperature and lower initial soil moisture caused a marked reduction in snowmelt runoff. Similarly, large reductions in streamflow discharge were caused by diminished winter precipitation, increased winter air temperature and decreased fall soil moisture content. A scenario showed that a combination of these factors could cause complete cessation of spring streamflow even under moderate drought of 15% reduction in winter precipitation and 2·5 °C increase in winter mean air temperature. Results show that spring runoff and streamflow discharge are inherently unstable in the Canadian prairie environment, and so, magnify the impacts of drought, and through multi‐season storage and vegetation change can cause the impacts of hydrological drought to persist for several seasons after meteorological drought has ended. Copyright © 2007 John Wiley &amp; Sons, Ltd.

Assessment of Irrigation Practice in Wheat at Farmers' Fields under Shallow Water Table Conditions through Simulation Model

The central and western part of Haryana underlain with brackish ground water quality has experienced rise of water table at a rate of 10 to 30 cm annually during the last three decades. On an average the area under critical water table depth (0-3.0 m) increased from 6.20 per cent in October 2002 to 10.61 percent in October 2003 and 10.27 per cent in October 2004. At present about 2 per cent area of the State is fully waterlogged (0-1.5m). Poor irrigation and drainage management and inadequate exploitation of saline ground water are the main factors responsible for this phenomenon. Physical based one-dimensional simulation model SWAP (Soil Water Atmosphere Plant) was employed to evaluate irrigation practice in wheat crop under shallow water table condition using field experimental data collected at farmers' fields. The field experiments were undertaken during rabi 2002-03 and 2003-04 at two sites having ground water quality EC = 4.5 and 5.5 d Sm·j for site I and site 2 respectively and different soil types (clay loam for site 1 and loam for site 2). The water table depth varied from 100-175 cm and 70-170 cm at site I and site 2 respectively during the crop growth season. Simulations were undertaken for both the sites to evaluate the impact of adopted irrigation practice by the farmers on crop performance and soil salinization/desalinization processes. The model provided all water and salt balance components during crop growth season. The water and salt balance component obtained for each simulation were used to derive Water Management Response Indicators (WMRI's) (Relative Evapotranspiration, Moisture Storage Change, Salinity Hazard Index and Saturation Index). The WMRI's were further used to evaluate the performance of the crop, changes in soil moisture storage and soil salinity under the shallow water table condition. The perusal of WMRI's indicated that the soil moisture in 0-2 m profile remained on higher side during crop season at both the experimental sites (Saturation Index = 0.75 to 0.86 for site I and 2 respectively). The simulation study further revealed that the crop performance was good at site I as indicated by relatively higher Relative Evapotranspiration (0.7) and low Salinity Hazard Index (0.65) but it was relatively poor at site ~ (Relative Evapotranspiration = 0.60 and Salinity Hazards Index = 0.9) due to late sown condition. It was suggested that provision of surface and sub-surface drainage system coupled with efficient irrigation application at farmers' fields could result in sustainable crop production by maintaining desirable soil moisture and solute concentration in the profile.

Impact of Atmospheric Moisture Storage on Precipitation Recycling

Abstract Computations of precipitation recycling using analytical models are generally performed under the assumption of negligible change in moisture storage in the atmospheric column. Because the moisture storage term is nonnegligible at smaller time scales, most recycling studies using analytical models are done at monthly or longer time scales. A dynamic precipitation recycling model, which incorporates the change in moisture storage, is developed. It is derived formally from the conservation of mass equation and is presented in a simple and computationally efficient form. This model allows for recycling analysis at a range of temporal scales, from daily to monthly and longer. In comparison to the traditional models that do not include the storage term, the new model presents almost identical spatial and temporal variability, but predicts recycling ratios that are 12%–33% larger at a monthly level. The dynamic model is used to study the variability of monthly precipitation recycling over the conterminous United States using Reanalysis-II data from 1979 to 2000. On average, the southeastern and southwestern parts of the country exhibit high summer recycling ratios, contrasting with the low values in the northeastern and northwestern United States. The Colorado region also presents high recycling ratios. Dominant modes of spatiotemporal variability in recycling are identified using EOF analysis. The first mode captures strong recycling ratios over the western United States during the summers of 1986, 1992, and 1998. The second mode captures anomalous high recycling ratios during 1988 and 1989 over the central part of the country, and anomalous low ratios during 1980 and 1993.

Evaluation of the hydrological components added to an atmospheric land-surface scheme

Discharge from a small grassland catchment in Ireland is simulated with the atmospheric land-surface scheme SEWAB. Hydrological processes are parameterized to represent surface runoff and baseflow generation and soil moisture storage changes. Surface ponding and infiltration are explicitly described in order to account for the rapid response of streamflow to precipitation events. The annual discharge, the evapotranspiration and individual flood flows are accurately modelled. The simulation of soil moisture at various depths is close to the observations from time domain reflectometer measurements. An analysis of the significance of individual hydrological processes for discharge simulation from the small catchment found the ponding process to be essential for time periods of less than 12 hours. A depth dependent saturation hydraulic conductivity improves the simulations on all time scales.

Pour mieux comprendre la radiothérapie

The water-balance components of 16 Soil–Vegetation Atmospheric Transfer (SVAT) schemes were evaluated by comparing predicted and observed streamflow, predicted evapotranspiration and evapotranspiration inferred from an atmospheric moisture budget analysis, and soil moisture storage changes for a seven-year period (1980–1986) using data from the Red–Arkansas River basins of the Southern Great Plains of the USA. The evaluations support the following suggestions: (a) The mean annual runoff of all models follows, at least generally, the strong climatic East–West gradient of precipitation, although most models predict too much runoff in the dry part of the basin. (b) The mean monthly storage change tends to be underestimated, even though all models capture reasonably well the seasonality of the evapotranspiration. (c) The wide range of conceptualizations used for generation of surface and subsurface runoff strongly affect runoff generation on seasonal, and shorter, time scales. Model responses to summer precipitation ranged from almost no summer runoff (one model) to the (more common) situation of persistent overprediction of summer runoff, especially in the driest part of the basin. (d) All models tended to underpredict evapotranspiration in summer and overpredict in winter. (e) Model-derived mean seasonal cycles of changes in soil moisture storage are qualitatively similar to those inferred from observations, but most models do not predict the decrease in April soil moisture storage and the increase in October that is inferred from observations.

The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) phase 2(c) Red–Arkansas River basin experiment:: 3. Spatial and temporal analysis of water fluxes

The water-balance components of 16 Soil–Vegetation Atmospheric Transfer (SVAT) schemes were evaluated by comparing predicted and observed streamflow, predicted evapotranspiration and evapotranspiration inferred from an atmospheric moisture budget analysis, and soil moisture storage changes for a seven-year period (1980–1986) using data from the Red–Arkansas River basins of the Southern Great Plains of the USA. The evaluations support the following suggestions: (a) The mean annual runoff of all models follows, at least generally, the strong climatic East–West gradient of precipitation, although most models predict too much runoff in the dry part of the basin. (b) The mean monthly storage change tends to be underestimated, even though all models capture reasonably well the seasonality of the evapotranspiration. (c) The wide range of conceptualizations used for generation of surface and subsurface runoff strongly affect runoff generation on seasonal, and shorter, time scales. Model responses to summer precipitation ranged from almost no summer runoff (one model) to the (more common) situation of persistent overprediction of summer runoff, especially in the driest part of the basin. (d) All models tended to underpredict evapotranspiration in summer and overpredict in winter. (e) Model-derived mean seasonal cycles of changes in soil moisture storage are qualitatively similar to those inferred from observations, but most models do not predict the decrease in April soil moisture storage and the increase in October that is inferred from observations.

Irrigation planning in wheat ( Triticum aestivum) under deep water table conditions through simulation modelling

Irrigation scheduling resulting in minimum percolation loss was optimized for a wheat crop under deep water table (15 m) conditions through the simulation model SWASALT (Soil, Water, Atmosphere, SALT), using a field experimental study of an area underlain by poor-quality groundwater. The line source sprinkler irrigation technique was adopted to create different irrigation regimes at different critical crop growth stages. The model was calibrated and validated by comparing observed and simulated soil moisture content at different depths (0–50 cm and 50–100cm), and observed and predicted crop yields. The concept of water management response indicators (WMRIs), i.e. relative transpiration ( T r = E t E tp ), transpiration efficiency ( T eff = E t ( Irr + P )), evapotranspiration efficiency ( ET eff = ET ( Irr + P )), moisture storage change ( MSC = (W harvest − W sowing ) W sowing ) and percolation index ( P i = Perc ( Irr + P )), was used to evaluate on-farm irrigation performance under different irrigation scenarios by carrying out simulations for two soil textures, i.e. sandy soil underlain by loamy sand (Type I) and sandy clay loam underlain by sandy loam (Type II). The WMRIs were based on water balance components for each simulation study (after calibration and validation of the model). The intersection of T r and T eff with minimum percolation loss was the criterion applied for selecting the optimum irrigation schedule. On this basis, the optimum irrigation schedules for soil Types I and II were found to be pre-sowing irrigation depth of 4 cm, ten subsequent post-sowing irrigations of 3 cm each with an interval of 11 days, and pre-sowing irrigation of 8 cm and four subsequent post-sowing irrigations (critical crop growth stages) of 6.5 cm each, respectively, and resulted in no percolation loss. For these schedules, the relative transpiration for soil Types I and II were 91% and 79%, respectively, and the corresponding soil water storage (deficit) values were 26.9% and 13% cent, respectively, with irrigation supply of 34cm. The simulation study further indicated that the percolation loss increased with greater irrigation application depths and resulted in inefficient use of soil moisture storage. Thus the on-farm water management strategy for areas underlain by brackish groundwater should be light but frequent itrigations for light textured soil as compared with medium textured soil to maintain optimum crop yield and hydrodynamic equilibrium.

Irrigation planning in cotton through simulation modeling

Experiments were undertaken at CCS Haryana Agricultural University Farm, Sirsa (India) to estimate the optimum irrigation schedule for cotton resulting in minimum percolation losses. The sprinkler line source technique was adopted for creating various irrigation regimes at different crop growth stages. The SWASALT (Simulation of Water And SALT) model after calibration and validation provided water balance components. The wa-ter management response indicators (WMRI's) such as transpiration efficiency Et/(Irr + P), relative transpiration Et/Etp, evapotranspiration efficiency ET/(Irr + P), soil moisture storage change ΔW/Wint (deficit/excess) and percolation loss Perc/(Irr. + P) were evaluated using water balance components as estimated by the simulation study. Under limited water supply conditions, the optimum irrigation depth was found to be 57 mm at crop growth stages with pre-sowing and 1st irrigation of 120 mm and 80 mm respectively for sandy clay loam underlain by sandy loam soil (Type I). The corresponding values of relative transpiration, transpiration efficiency and evapotranspiration efficiency were 0.65, 0.65 and 0.89 respectively. The crop yield varied linearly with increasing irrigation depth which was evident from increase in relative transpiration with increasing depth of water application. However, increased depth of irrigation resulted in less moisture utilisation from soil storage (20% depletion at 40 mm depth and 4.4% moisture built up at 100 mm depth). The extended simulation study for sandy soil underlain by loamy sand (Type II) indicated that two pre-sowing irrigations each 40 mm and subsequent irrigations of 40 mm at an interval of 20 days depending upon rainfall were optimum. This irrigation scenario resulted in zero percolation loss accompanied by 74% relative transpiration and 14 per cent soil moisture depletion.