AN ASSESSMENT OF THE CAPABILITY OF A COMPUTER PROGRAM TO ESTIMATE FALL SOIL MOISTURE AND DEEP PERCOLATION

1976 ◽  
Vol 56 (4) ◽  
pp. 357-362 ◽  
Author(s):  
J. C. VAN SCHAIK ◽  
D. S. CHANASYK ◽  
E. H. HOBBS
Keyword(s):  
Soil Moisture ◽  
Computer Program ◽  
Root Zone ◽  
Deep Drainage ◽  
Soil Moisture Storage ◽  
Moisture Contents ◽  
Growing Seasons ◽  
Actual Field ◽  
Moisture Storage ◽  
Summer Fallow

A computer program that estimates changes in soil moisture was used to calculate fall soil moisture contents and possible deep drainage. Generally good agreement was obtained between the calculated and measured total moisture contents under continuous wheat and grass after each of four and six growing seasons, respectively. Estimates of soil moisture storage and deep drainage under summer fallow showed discrepancies because unsaturated moisture flow was not included in the model. However, a comparison of actual field and estimated moisture data indicated that in two of five growing seasons, 3.7–7.5 cm of water could have been lost from the root zone of fallowed land because of deep drainage.

scholarly journals A Prior Estimation of the Spatial Distribution Parameter of Soil Moisture Storage Capacity Using Satellite-Based Root-Zone Soil Moisture Data

2019 ◽  
Vol 11 (21) ◽  
pp. 2580 ◽  
Author(s):  
Yifei Tian ◽  
Lihua Xiong ◽  
Bin Xiong ◽  
Ruodan Zhuang
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Storage Capacity ◽  
Spatial Information ◽  
Root Zone ◽  
River Catchment ◽  
Soil Moisture Storage ◽  
Soil Moisture Data ◽  
Moisture Storage ◽  
The Impact

Integration of satellite-based data with hydrological modelling was generally conducted via data assimilation or model calibration, and both approaches can enhance streamflow predictions. In this study, we assessed the feasibility of another approach that uses satellite-based soil moisture data to directly estimate the parameter β to represent the degree of the spatial distribution of soil moisture storage capacity in the semi-distributed Hymod model. The impact of using historical root-zone soil moisture data from the Soil Moisture Active Passive (SMAP) mission on the prior estimation of the parameter β was explored. Two different ways to incorporate the root-zone soil moisture data to estimate the parameter β are proposed, i.e., one is to derive a priori distribution of β , and the other is to derive a fixed value for β . The simulations of the Hymod models employing the two ways to estimate β are compared with the results produced by the original model, i.e., the one without employing satellite-based data to estimate the parameter β , at three study catchments (the Upper Hanjiang River catchment, the Xiangjiang River catchment, and the Ganjiang River catchment). The results illustrate that the two ways to incorporate the SMAP root-zone soil moisture data in order to predetermine the parameter β of the semi-distributed Hymod model both perform well in simulating streamflow during the calibration period, and a slight improvement was found during the validation period. Notably, deriving a fixed β value from satellite soil moisture data can provide better performance for ungauged catchments despite reducing the model freedom degrees due to fixing the β value. It is concluded that the robustness of the Hymod model in predicting the streamflow can be improved when the spatial information of satellite-based soil moisture data is utilized to estimate the parameter β .

scholarly journals Influence of Various Soil and Water Conservation Methods on the Moisture Balance at Coffee Plant Root Zone

2022 ◽  
Author(s):  
Lina Saraswati ◽  
Sugeng Prijono ◽  
Budi Prasetya
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Conservation ◽  
Root Zone ◽  
Dry Season ◽  
Soil And Water Conservation ◽  
Soil Moisture Storage ◽  
Moisture Balance ◽  
Moisture Storage ◽  
Soil And Water

Background: The study of the moisture balance can be used to suppose the plants water requirement and the plants water use efficiency. The moisture balance influenced by climate factor, therefore climate change can affect the moisture balance especially in rainfed. Therefore, an effort is needed to manage soil moisture in rainfed as a climate change mitigation measure: soil and water conservation. This study aimed to determine the influence of soil and water conservation on the moisture balance in the coffee root zone. Methods: This study was conducted at people’s coffee plantation of Argotirto village, Sumbermanjing Wetan District, Malang Regency, located between 8.2411-8.1443 S and 112.4031-112.4634 E. Observation were made on February to November 2020, divided into observations in the wet season, dry seasons and flowering period. The observation plots consisted of terraced plot (P0), terraced + straight silt pit (P1), terraced + L-shaped silt pit (P2) and terrace + biopore (P3). The observation variables were: soil physical characteristics and moisture balance components there were precipitation, percolation, runoff, evapotranspiration and soil moisture storage. Result: At P1, the runoff depth was 80.89% lower and the percolation was 44.22% higher than P0. The total soil moisture storage at P1 was 20.06% higher than P0 in the dry season, indicating that P1 could increase the period of surplus moisture in the dry season.

scholarly journals The Normalized Difference Infrared Index (NDII) as a proxy for soil moisture storage in hydrological modelling

2015 ◽  
Vol 12 (8) ◽  
pp. 8419-8457 ◽  
Author(s):  
N. Sriwongsitanon ◽  
H. Gao ◽  
H. H. G. Savenije ◽  
E. Maekan ◽  
S. Saengsawang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Root Zone ◽  
Hydrological Modelling ◽  
Dry Season ◽  
Leaf Water ◽  
Wet Season ◽  
Exponential Relationship ◽  
Temporal And Spatial Distribution ◽  
Soil Moisture Storage ◽  
Moisture Storage

Abstract. With remote sensing we can readily observe the Earth's surface, but looking under the surface into the root zone of vegetation is still a major challenge. Yet knowledge on the dynamics of soil moisture in the root zone is essential for agriculture, land–atmosphere interaction and hydrological modelling, alike. In this paper we develop a novel approach to monitor the soil moisture storage deficit in the root zone of vegetation, by using the remotely sensed Normalised Difference Infrared Index (NDII) in the Upper Ping River Basin (UPRB) in northern Thailand. Satellite data from the Moderate Resolution Imaging Spectro-radiometer (MODIS) was used to evaluate the NDII over an 8 day period, covering the study area from 2001 to 2013. The results show that NDII values decrease sharply at the end of the wet season in October and reach lowest values near the end of the dry season in March. The values then increase abruptly after rains have started, but vary in an insignificant manner from the middle to the late rainy season. The NDII proves to be a very strong proxy for moisture storage deficit in the root zone, which is a crucial component of hydrological models. In addition, the NDII appears to be a reliable indicator for the temporal and spatial distribution of drought conditions in the UPRB. The 8 day average NDII values were found to correlate very well with the 8 day average soil moisture content (SU) simulated by FLEXL (rainfall–runoff model) at 8 runoff stations during the dry season – giving an average R2 value 0.87 on an exponential relationship, while for the wet season it reduced to be around 0.61. Apparently, the NDII is an effective index for the moisture storage in the root zone during the time of moisture deficit, and a powerful indicator to assess droughts. In the dry season, when plants are exposed to water stress, the leaf-water deficit increases steadily. Once leaf-water is close to saturation – mostly at the end of the wet season – leaf characteristics and NDII values do not vary significantly, causing lower correlation between NDII and Su in the wet season. However, the correlations between NDII and Su still remain high for both seasons and therefore the product can be used to define drought situations throughout the year and be of use to water management.

Dark Island heath (Ninety-mile Plain, South Australia). V. The water relationships in heath vegetation and pastures on the Makin sand

1957 ◽  
Vol 5 (2) ◽  
pp. 151 ◽  
Author(s):  
RL Specht
Keyword(s):  
Soil Moisture ◽  
Balance Sheet ◽  
South Australia ◽  
Field Capacity ◽  
Severe Drought ◽  
Soil Moisture Storage ◽  
Drought Conditions ◽  
Moisture Storage ◽  
Medicago Sativa L ◽  
Soil Moisture Status

Heath vegetation shows a major flush of growth during the mediterraneantype summer season, a time when calculations of the soil moisture storage by the techniques of Thornthwaite (1948) or Prescott, Collins, and Shirpurkar (1952) indicate that severe drought conditions should oocur. Monthly observations on the moisture status of the Makin sand under heath vegetation and, for comparison, under various pastures are therefore recorded. The problems of obtaining an accurate water balance-sheet for such a heterogeneous vegetation as the heath are discussed. Difficulties in the use of the various techniques for measuring soil moisture in sand, which has a low pF of 1.85 at field capacity, are enumerated. The following relationships were found between the evapotranspiration index (Itr = Etr / Ew0.75) and the available water (W). These data were calculated for 6 ft of sand. (i) Heath vegetation (10–14 years old) log (2.4–Itr) = 0.420–0.0383 W (ii) Heath vegetation (burnt) log (2.4–Itr) = 0.461–0.0380 W (iii) Oenothera odorata Jacq. pasture log (2.4–Itr) = 0.395–0.0269 W (iv) Medicago sativa L. pasture log (2.4–Itr) = 0.390–0.0270 W (v) Ehrharta calycina Sm. pasture log (2.4–Itr) = 0.400–0.0339 W From these equations the mean monthly quantities of rainfall which may be stored in 6 ft of sand under the various treatments described were calculated. Drought conditions are shown to occur in December and January, but are relieved in the later months of summer. Even if the stored moisture below 8 ft is considered, the soil moisture status would be expected to be just sufficient to maintain the vegetation in a "dormant" state, and yet the major growth of the heath vegetation occurs at this time. The calculated mean annual values of Itr range from 0.53 to 0.60 for these perennial communities. Close approximations to the actual soil moisture status can be obtained by substituting these values for K in Prescott's formula for potential evaporation, i.e. Etr = K x Ew0.75. Supplementary data on transpiration, growth, and the root systems of the pastures are also included.

Better placement of soil moisture point measurements guided by 2D resistivity tomography for improved irrigation scheduling

Soil Research ◽  
2011 ◽  
Vol 49 (6) ◽  
pp. 504 ◽  
Author(s):  
B. F. J. Kelly ◽  
R. I. Acworth ◽  
A. K. Greve
Keyword(s):  
Soil Moisture ◽  
Spatial Information ◽  
Root Zone ◽  
Irrigation Scheduling ◽  
Measurement Methods ◽  
Deep Drainage ◽  
Resistivity Tomography ◽  
Point Measurement ◽  
Irrigated Crops ◽  
2D Resistivity

Soil moisture beneath irrigated crops has traditionally been determined using point measurement methods such as neutron probes or capacitance systems. These approaches cannot measure soil moisture at depths beyond the root-zone of plants and have limited lateral coverage. It is shown that surface two-dimensional electrical resistivity tomography (ERT) can be used to map the spatial heterogeneity in soil moisture throughout a field under irrigated cotton. The case study demonstrates that ERT provides a better understanding of the pathways of water migration, and provides spatial information on how water storage changes throughout the growing season. We conclude that ERT should be integrated into farm water management surveys to delineate zones of excessive water loss due to deep drainage and to improve the positioning of point measurement methods for measuring soil moisture, thereby improving irrigation scheduling.

Soil water balance and evapotranspiration of irrigated cotton

1967 ◽  
Vol 69 (1) ◽  
pp. 95-101 ◽  
Author(s):  
W. R. Stern
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Balance Equation ◽  
Dry Season ◽  
Soil Water Balance ◽  
Wet Season ◽  
Water Balance Equation ◽  
Soil Moisture Storage ◽  
Moisture Storage

In a series of five irrigated cotton sowings (T2, T7, T9, T11, T14) evapotranspiration (Et) was determined for the period between October 1961 and October 1962 by observing frequently the changes in soil moisture storage, calculating through drainage, and solving for evapotranspiration in the water balance equation. Thus a water balance was obtained for each sowing extending over the entire crop.The average evapotranspiration in wet season sowings was of the order of 6·5 mm day−1 and in dry season sowings of the order of 4·5 mm day−1. The highest evapotranspiration values ranged between 10 and 12 mm day−1 in T2, T7 and T9 and between 7 and 9·5 mm day−1 in T11 and T14.

scholarly journals DESAIN INSTALASI PENGOLAHAN LEACHATE (IPL) DI TPA ENTIKONG KABUPATEN SANGGAU

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
YENDI FRIADI
Keyword(s):  
Soil Moisture ◽  
Constructed Wetland ◽  
Soil Moisture Storage ◽  
Run Off ◽  
Moisture Storage ◽  
Unit Unit

ABSTRAK Leachate dapat didefinisikan sebagai cairan yang menginfiltrasi melalui tumpukan sampah dan telah mengekstraksi material terlarut maupun tersuspensi. Sistem instalasi pengolahan leachate bergantung pada debit dan karaktersitik leachate itu sendiri. Tujuan dari penelitian ini adalah memperkirakan debit leachate yang dihasilkan oleh TPA Entikong sebagai acuan dasar perancangan/desain instalasi pengolahan leachate, merencanakan sistem instalasi pengolahan  leachate di TPA Entikong Kabupaten Sanggau serta mengetahui anggaran biaya yang diperlukan dalam perancangan IPL berdasarkan sistem pengolahan yang digunakan.Tahapan untuk mengolah dan menghitung data meliputi perhitungan debit leachate dan mendesain/merancang IPL. Debit leachate dihitung dari rata-rata hujan maksimum bulanan, dari data beberapa tahun atau dengan menggunakan metode neraca air yaitu metode pendekatan Thornhtwaite. Faktor-faktor yang berpengaruh terhadap kuantitas leachate dalam metode neraca air ini adalah presipitasi, evapotransipitasi, surface run-off dan soil moisture storage. Proses desain IPL terdiri dari penentuan letak IPL, penentuan jenis pengolahan, penentuan sistem pengolahan yang ada di Indonesia, pemilihan desain IPL, melakukan perhitungan hidroulik terhadap desain sistem IPL terpilih, menentukan layout bangunan IPL, membuat gambar rancangan, perhitungan anggaran biaya serta membuat spesifikasi teknis pembuatan IPL.Berdasarkan hasil perhitungan menggunakan metode Thornthwaite didapat perkolasi tertinggi sebesar 185,43 mm dan diketahui luas area timbunan sampah TPA Entikong sebesar 1,06 Ha maka diperoleh nilai debit leachate sebesar 65,52 m3/hari. Kandungan organik (BOD) yang terdapat dalam leachate mempunyai nilai BOD sebesar 10.000 mg/L, sehingga metode pengolahan biologi sangat tepat digunakan untuk mengolah leachate di TPA Entikong. Sistem pengolahan yang digunakan adalah pengolahan secara biologi. Unit-unit pengolahan leachate TPA Entikong yang direncanakan adalah bak ekualisasi,  kolam anaerobik, kolam fakultatif, kolam maturasi dan constructed wetland. Besarnya total biaya yang dibutuhkan adalah Rp. 1.375.000.000,00 Kata-kata kunci : BOD, Leachate, Thornthwaite

Seasonal Movement PAtterns of the Eastern Grey Kangaroo in Southern Queensland

1982 ◽  
Vol 9 (3) ◽  
pp. 373 ◽  
Author(s):  
GJE Hill
Keyword(s):  
Soil Moisture ◽  
Seasonal Changes ◽  
Movement Patterns ◽  
Distribution Patterns ◽  
Faecal Pellet ◽  
Soil Moisture Storage ◽  
Seasonal Movement ◽  
Grey Kangaroo ◽  
Pellet Counts ◽  
Moisture Storage

A 2-y study was made of seasonal movement patterns of the eastern grey kangaroo, Macropus giganteus Shaw, in the Warwick district of south-eastern, and the Bollon district of south-western, Queensland. Faecal pellet counts were used to obtain indices of kangaroo usage of cleared country adjacent to cover. Kangaroos were sensitive to changes in forage status, particularly pasture phenology. As quality and quantity of forage reserves declined, animals made progressively greater use of cleared areas. This resulted in marked seasonal changes in distribution patterns. Of the variables quantified (rainfall, soil moisture storage and pasture growth), rainfall provided the best correlations with kangaroo usage of cleared country, explaining 55% (P = 0.002) of the variation in distribution at Warwick and 91% (P = 0.001) of that at Bollon.

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