The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset II: Land use, hydrology and sediment production monitoring in Houay Pano, northern Lao PDR

Abstract

Mountain regions of the humid tropics are characterized by steep slopes and heavy rains. These regions are thus prone to both high surface runoff and soil erosion. In Southeast Asia, uplands are also subject to rapid land-use change, predominantly as a result of increased population pressure and market forces. Since 1998, the Houay Pano site, located in northern Lao PDR (19.85 N 102.17 E) within the Mekong basin, aims at assessing the long-term impact of the conversion of traditional slash-and-burn cultivation systems to commercial perennial monocultures such as teak tree plantations, on the catchment hydrological response and sediment yield. The instrumented site monitors hydro-meteorological and soil loss parameters at both microplot (1 m 2 ) and small catchment (0.6 km 2 ) scales. The monitored catchment is part of the network of critical zone observatories named Multiscale TROPIcal CatchmentS (M-TRO-PICS). The data shared by M-TROPICS in Houay Pano are (1) rainfall, (2) air

The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset III: Hydro‐geochemical monitoring of the Mule Hole catchment, south India

“…The overarching goal of M‐TROPICS is to assess the response of tropical catchments to global change. M‐TROPICS includes six experimental catchments located in the tropical belt and encompassing a wide gradient of climates, bedrock types, topographies, and land‐use conditions: the Nyong basin and its nested Nsimi catchment in Cameroun (Audry et al, 2021, this special issue), the Houay Pano catchment in Lao PDR (Boithias et al, 2021, this special issue), the Dong Cao catchment in Vietnam, the Huay Ma Nai catchment in Thailand, and the Berambadi and the Mule Hole catchments in India.…”

In-stream <i>Escherichia coli</i> modeling using high-temporal-resolution data with deep learning and process-based models

“…The study area is the 0.6 km 2 Houay Pano headwater catchment, located 10 km south of the city of Luang Prabang, Lao PDR (Boithias et al, 2021a) (Fig. 1).…”

“…Worldwide, pathogens tend to wreak havoc on human health because of the diseases they cause, such as diarrhea, resulting in infant mortality. In particular, developing countries are vulnerable to pathogen-related diseases due to the deficit of sanitation facilities (Boithias et al, 2016). Escherichia coli (E. coli) has been frequently used as an indicator of fecal bacteria because it is easy to culture (Rochelle-Newall et al, 2015).…”

“…Popular models to simulate E. coli are the Soil and Water Assessment Tool (SWAT) (Neitsch et al, 2011), Hydrological Simulation Program-FORTRAN (HSPF) (Bicknell et al, 1997), INCA-Pathogens (Whitehead et al, 2016), and pathogen catchment budget (PCB) (Ferguson et al, 2007). The fate and transport of E. coli are a complex phenomenon with several drivers (Pachepsky et al, 2018), such as the hydrological regime (Boithias et al, 2016;Pachepsky et al, 2017), contributions of both surface runoff and subsurface flow to the overall instream discharge (Boithias et al, 2021b), concentration and sources of suspended sediment (Ribolzi et al, 2016;Nguyen et al, 2016), land use (Causse et al, 2015;Nakhle et al, 2021), intrinsic properties of the bacterium (Pachepsky et al, 2014), and economic conditions (Iqbal et al, 2019). Recently, Sowah et al (2020) applied the SWAT model to research the sources and drivers of E. coli in the Clouds Creek watershed, USA.…”

Overland flow during a storm event strongly affects stream water chemistry and bacterial community structure

“…The catchment is part of the M-TROPICS network of instrumented catchments (Boithias et al 2021b). Three hydrometric stations that allowed continuous monitoring of stream discharge and water sampling at the outlet of three nested catchments were selected for this work (Fig.…”