Peat Soil Moisture Research Articles

The technique for satellite monitoring of peatlands in order to determinate their fire hazard and combustion risks

Prolonged dry periods in spring and autumn, which are becoming more frequent for the Ukrainian Polissya, contribute to fires, especially in peatlands, that are dangerous for human health and ecosystems in general. Forecasting the risk of such natural and anthropogenic emergencies requires monitoring of current situations. Satellite monitoring provides an accurate information of the disaster and allows to realistically estimate the amount of damage. The article investigates the factors to be taken into account in peatlands monitoring and considers methods of processing of multispectral satellite data (Landsat, Sentinel series) in combination with traditional statistics data and field measurements. The technological diagram for making the studies is proposed. To assess the risks, the values that can be obtained simultaneously with the help of satellite data on large areas are determined: peat soil moisture, peat surface temperature, spectral indices (water, soil), evapotranspiration; the seasons of the greatest risks of fires are defined, and also risks associated with anthropogenic impact (proximity to settlements, agricultural trials, hayfields, careless handling of fire and arson). The condition of peatlands is diagnosed according to the developed criteria and assessed by four levels of fire risk - critical, high, low and insignificant. The study of spectral indices showed that with the help of the SAVI soil index in combination with the analysis of surface temperature, the burned areas and fires are accurately mapped in real-time. To predict the occurrence of fire situations, the use of two variants of the normalized differential water index (NDWI) in combination with thermal imaging is proposed. The test sites provide examples of diagnosing fires and burned areas in peatlands, as well as examples of forecasting fire hazards situations that require close attention of local authorities. Recommendations are given to prevent emergencies related to the burning of peatlands.

Sistem Monitor Suhu dan Kelembaban Berbasis Cloud pada Lahan Gambut

The Research and Development Center for The Soil and Agricultural Land Resources Office estimates that Indonesia's peatland area is around 14.9 million H. In the dry season, peatlands experience dryness, so they burn easily. More than 99% of the causes of forest and peatland fires are human-made, either deliberately burning or neglecting to use fire. IoT (Internet of Things) technology is used to connect all devices to the internet and enable communication of each other, one reason for which is that digital data stored on cloud storage, then display the data on a website. The website was designed to monitor the peat's condition by considering the peat's air temperature, peat soil temperature, peat soil moisture, and humidity around the peatlands. IoT retrieves and sends data to the cloud, then websites retrieve and display data from the cloud in diagram and table format for easy reading of monitors. Website monitoring systems utilize several components, including domains as addresses, web hosting as web data storage, and the CMS framework CodeIgniter is used as the basis of the application. Sending data from IoT to web hosting requires cloud storage. Without this, it is necessary to transfer data from the IoT to the website manually. The monitor system can read temperature and humidity sensor data, store it in the cloud, then display it on a website so that the data monitoring process runs well.

A new indicator of forest fire risk for Indonesia based on peat soil reflectance spectra measurements

ABSTRACT Conventional fire risk prediction using vegetation indexes is inappropriate because changes in soil moisture caused by plant drought stress have a 1 to 2 month time lag, which is too long for fire risk management. Further, soil and water indices used for traditional bare land assessments are also unsuitable because Indonesia is partially covered by peat soil, which has different reflection characteristics compared to typical agricultural and field soils. Here we describe a new index for estimating peat soil moisture using satellite remote sensing data. The method was developed using the ultra-blue band (435 to 451 nm) of the Land Remote-Sensing Satellite (Landsat 8) and is based on the moisture dependence of the reflected spectra measured directly. Our developed index showed a relatively strong correlation (r = 0.56 to 0.63) with real wildfire points and was a more reliable index than conventional measures used for fire risk management.

Pengaruh Fluktuasi Muka Air Tanah Terhadap Pelepah Bawah Mengering (Low Frond Desiccation) Kelapa Sawit di Lahan Gambut Labuhan Batu, Sumatera Utara

Masalah tanaman kelapa sawit berupa kering pelepah bagian bawah (low frond desiccation/LFD) sering terjadi pada lahan gambut. Kejadian ini umumnya dikaitkan dengan kondisi fluktuasi muka air tanah gambut yang berpengaruh terhadap kelembaban tanah gambut dan ketersediaan serta serapan hara oleh tanaman. Penelitian ini bertujuan untuk mengkaji permasalahan LFD, faktor-faktor penyebab dan upaya pencegahan atau pemulihannya. Kajian LFD telah dilakukan di perkebunan kelapa sawit di lahan gambut daerah Labuhan Batu, Sumatera Utara. Pengamatan meliputi fluktuasi muka air tanah, kondisi kelembaban tanah, sifat kimia tanah, serapan hara daun, pertumbuhan dan produksi tanaman dilakukan pada blok tanaman normal dan blok tanaman mengalami LFD. Hasil penelitian menunjukkan bahwa terjadinya penurunan muka air tanah gambut secara drastis pada saat bulan kering berdampak terhadap penurunan kelembaban gambut, bahkan hingga tanah gambut mengering. Kondisi pengeringan gambut menyebabkan ketersediaan hara dalam tanah dan serapan hara menurun secara nyata, sehingga memicu terjadinya LFD. Serapan hara tanaman yang mengalami LFD berat menurun dengan kisaran penurunan sebesar 25 – 41% untuk hara makro dan 22 – 53% untuk serapan hara mikro. Kondisi LFD berat secara nyata menurunkan pertumbuhan dan produksi tanaman kelapa sawit. Penurunan produksi dapat mencapai 27% per tahun dibandingkan dengan tanaman normal. Tanaman mengalami LFD dapat berangsur pulih dengan penerapan water management yang efektif, kontinyu dan terkontrol melalui pengelolaan muka air tanah pada kisaran kedalaman 40-60 cm pada blok tanaman.

Transition from a warm and dry to a cold and wet climate in NE China across the Holocene

Northeast (NE) China lies in the northernmost part of the East Asian Summer monsoon (EASM) region. Although a series of Holocene climatic records have been obtained from lakes and peats in this region, the Holocene hydrological history and its controls remain unclear. More specifically, it is currently debated whether NE China experienced a dry or wet climate during the early Holocene. Here we reconstruct changes in mean annual air temperature and peat soil moisture across the last ∼13,000 year BP using samples from the Gushantun and Hani peat, located in NE China. Our approach is based on the distribution of bacterial branched glycerol dialkyl glycerol tetraethers (brGDGTs) and the abundance of the archaeal isoprenoidal (iso)GDGT crenarchaeol. Using the recently developed peat-specific MAATpeat temperature calibration we find that NE China experienced a relatively warm early Holocene (∼5–7 °C warmer than today), followed by a cooling trend towards modern-day values during the mid- and late Holocene. Moreover, crenarchaeol concentrations, brGDGT-based pH values, and the distribution of 6-methyl brGDGTs, all indicate an increase in soil moisture content from the early to late Holocene in both peats, which is largely consistent with other data from NE China. This trend towards increasing soil moisture/wetter conditions across the Holocene in NE China records contrasts with the trends observed in other parts of the EASM region, which exhibit an early and/or mid-Holocene moisture/precipitation maximum. However, the Holocene soil moisture variations and temperature–moisture relationships (warm–dry and cold–wet) observed in NE China are similar to those observed in the core area of arid central Asia which is dominated by the westerlies. We therefore propose that an increase in the intensity of the westerlies across the Holocene, driven by increasing winter insolation, expanding Arctic sea ice extent and the enhanced Okhotsk High, caused an increase in moisture during the late Holocene in NE China.

Performance of Fire Risk Estimates Based on Soil Moisture of Selected Peat Land Use

Each peat land used has a different vegetation that will influences peat soil moisture during dry seasons. The level of fire risk depends on peat soil moisture in every land used. The objective of this research was to evaluate the variability of peat soil moisture at different peat land used during dry season and its impact on fire risk The research was carried on peat land with four types of land used located Sub District of Pedamaran, Ogan Komering Ilir District South Sumatera Province was held from June 2018 to July 2018. We investigated soil moisture variability in this site to a depth 30 cm under four type of peat land used during dry season 2018. The result of the research showed that on the second month of the dry season all peat soil to 30 cm depth have soil moisture category moderate fire risk except on secondary forest category at low risk fire. The higher fire risk of the land used the more attention we must focus to prevent the fire.

High heterotrophic CO2 emissions from a Malaysian oil palm plantation during dry-season

Tropical peatlands are currently being rapidly cleared and drained for the establishment of oil palm plantations, which threatens their globally significant carbon sequestration capacity. Large-scale land conversion of tropical peatlands is important in the context of greenhouse gas emission factors and sustainable land management. At present, quantification of carbon dioxide losses from tropical peatlands is limited by our understanding of the relative contribution of heterotrophic and autotrophic respiration to net peat surface CO2 emissions. In this study we separated heterotrophic and autotrophic components of peat CO2 losses from two oil palm plantations (one established in ‘2000’ and the other in 1978, then replanted in ‘2006’) using chamber-based emissions sampling along a transect from the rooting to non-rooting zones on a peatland in Selangor, Peninsular Malaysia over the course of 3 months (June–August, 2014). Collar CO2 measurements were compared with soil temperature and moisture at site and also accompanied by depth profiles assessing peat C and bulk density. The soil respiration decreased exponentially with distance from the palm trunks with the sharpest decline found for the plantation with the younger palms with overall fluxes of 1341 and 988 mg CO2 m−2 h−1, respectively, at the 2000 and 2006 plantations, respectively. The mean heterotrophic flux was 909 ± SE 136 and 716 ± SE 201 mg m−2 h−1 at the 2000 and 2006 plantations, respectively. Autotrophic emissions adjacent to the palm trunks were 845 ± SE 135 and 1558 ± SE 341 mg m−2 h−1 at the 2000 and 2006 plantations, respectively. Heterotrophic CO2 flux was positively related to peat soil moisture, but not temperature. Total peat C stocks were 60 kg m−2 (down to 1 m depth) and did not vary among plantations of different ages but SOC concentrations declined significantly with depth at both plantations but the decline was sharper in the second generation 2006 plantation. The CO2 flux values reported in this study suggest a potential for very high carbon (C) loss from drained tropical peats during the dry season. This is particularly concerning given that more intense dry periods related to climate change are predicted for SE Asia. Taken together, this study highlights the need for careful management of tropical peatlands, and the vulnerability of their carbon storage capability under conditions of drainage.

On the applicability of unimodal and bimodal van Genuchten–Mualem based models to peat and other organic soils under evaporation conditions

Summary Soil moisture is one of the key parameters controlling biogeochemical processes in peat and other organic soils. To understand and accurately model soil moisture dynamics and peatland hydrological functioning in general, knowledge about soil hydraulic properties is crucial. As peat differs in several aspects from mineral soils, the applicability of standard hydraulic functions (e.g. van Genuchten–Mualem model) developed for mineral soils to peat soil moisture dynamics might be questionable. In this study, the hydraulic properties of five types of peat and other organic soils from different German peatlands have been investigated by laboratory evaporation experiments. Soil hydraulic parameters of the commonly-applied van Genuchten–Mualem model and the bimodal model by Durner (1994) were inversely estimated using HYDRUS-1D and global optimization. The objective function included measured pressure heads and cumulative evaporation. The performance of eight model set-ups differing in the degree of complexity and the choice of fitting parameters were evaluated. Depending on the model set-up, botanical origin and degree of peat decomposition, the quality of the model results differed strongly. We show that fitted ‘tortuosity’ parameters τ of the van Genuchten–Mualem model can deviate very much from the default value of 0.5 that is frequently applied to mineral soils. Results indicate a rather small decrease of the hydraulic conductivity with increasing suction compared to mineral soils. Optimizing τ did therefore strongly reduce the model error at dry conditions when high pressure head gradients occurred. As strongly negative pressure heads in the investigated peatlands rarely occur, we also reduced the range of pressure heads in the inversion to a ‘wet range’ from 0 to −200 cm. For the ‘wet range’ model performance was highly dependent on the inclusion of macropores. Here, fitting only the macropore fraction of the bimodal model as immediately drainable additional pore space seems to be a practical approach to account for the macropore effect, as the fitting of the full bimodal model led to only marginal further improvement of model performance. This keeps the number of parameters low and thus provides a model that is more easily managed in pedotransfer function development and practical applications like large scale simulations. Our findings point out first options to improve the performance of the frequently-used simple single-domain models when they are applied to organic soils. We suggest further performance evaluation of these models during wetting periods when they are known to fail to describe preferential and non-equilibrium flow phenomena.

Nitrate and sulphate dynamics in peat subjected to different hydrological conditions: Batch experiments and field comparison

Summary Conservation of ecosystems that depend on water management and water quality has to be considered. We combined a field monitoring and batch experiments to better understand the impact of hydrological perturbations on peatland functioning. Factors influencing the dynamics of nitrate and sulphate concentration observed in two sites with different hydrological conditions in a south Normandy peatland were determined through the comparison of field and lab experiment. The effects of nitrate input, and oxic or anoxic conditions on nitrate and sulphate concentrations were investigated in bioreactors, using peat samples from field sites influenced by different hydrologic regimes. In this experiment, peat samples were subjected to similar conditions to address the effects of NO 3 - and O2 concentrations (chemical effects), and the effect of hydrologic regimes and peat soil moisture (physical effects) on nitrate and sulphate dynamics. Cl−, SO 4 2 - and NO 3 - were monitored for 215 h. Nitrate was significantly reduced in most experiments. A complete nitrate reduction after 215 h in soil under anoxic conditions was observed. A denitrification process was also found under aerobic conditions depending on the peat site sampling, i.e. depending on the hydrological conditions. This process was interpreted as a heterotrophic denitrification. Sulphate monitoring revealed that 400 mg L−1 were produced in peat from the peat site with high hydrologic fluxes under aerobic conditions. Clear differences in chloride concentration (deviance analysis, P

Monitoring the effect of restoration measures in Indonesian peatlands by radar satellite imagery

In the context of the ongoing climate change discussions the importance of peatlands as carbon stores is increasingly recognised in the public. Drainage, deforestation and peat fires are the main reasons for the release of huge amounts of carbon from peatlands. Successful restoration of degraded tropical peatlands is of high interest due to their huge carbon store and sequestration potential. The blocking of drainage canals by dam building has become one of the most important measures to restore the hydrology and the ecological function of the peat domes. This study investigates the capability of using multitemporal radar remote sensing imagery for monitoring the hydrological effects of these measures. The study area is the former Mega Rice Project area in Central Kalimantan, Indonesia, where peat drainage and forest degradation is especially intense. Restoration measures started in July 2004 by building 30 large dams until June 2008. We applied change detection analysis with more than 80 ENVISAT ASAR and ALOS PALSAR images, acquired between 2004 and 2009. Radar signal increases of up to 1.36 dB show that high frequency multitemporal radar satellite imagery can be used to detect an increase in peat soil moisture after dam construction, especially in deforested areas with a high density of dams. Furthermore, a strong correlation between cross-polarised radar backscatter coefficients and groundwater levels above −50 cm was found. Monitoring peatland rewetting and quantifying groundwater level variations is important information for vegetation re-establishment, fire hazard warning and making carbon emission mitigation tradable under the voluntary carbon market or REDD (Reducing Emissions from Deforestation and Degradation) mechanism.

Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

Abstract. In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K-nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it should not be ignored as a potential modeling technique for hydrological applications.

Carbon exchange of grazed pasture on a drained peat soil

AbstractLand‐use changes have contributed to increased atmospheric CO2 concentrations. Conversion from natural peatlands to agricultural land has led to widespread subsidence of the peat surface caused by soil compaction and mineralization. To study the net ecosystem exchange of carbon (C) and the contribution of respiration to peat subsidence, eddy covariance measurements were made over pasture on a well‐developed, drained peat soil from 22 May 2002 to 21 May 2003. The depth to the water table fluctuated between 0.02 m in winter 2002 to 0.75 m during late summer and early autumn 2003. Peat soil moisture content varied between 0.6 and 0.7 m3 m−3 until the water table dropped below 0.5 m, when moisture content reached 0.38 m3 m−3. Neither depth to water table nor soil moisture was found to have an effect on the rate of night‐time respiration (ranging from 0.4–8.0 μmol CO2 m−2 s−1 in winter and summer, respectively). Most of the variance in night‐time respiration was explained by changes in the 0.1 m soil temperature (r2=0.93). The highest values for daytime net ecosystem exchange were measured in September 2002, with a maximum of −17.2 μmol CO2 m−2 s−1. Grazing events and soil moisture deficiencies during a short period in summer reduced net CO2 exchange. To establish an annual C balance for this ecosystem, non‐linear regression was used to model missing data. Annually integrated (CO2) C exchange for this peat–pasture ecosystem was 45±500 kg C ha−1 yr−1. After including other C exchanges (methane emissions from cows and production of milk), the net annual C loss was 1061±500 kg C ha−1 yr−1.